Expanding electric vehicle (EV) charging infrastructure is essential for transitioning to an electrified mobility system. With rising EV adoption rates, firms face increasing regulatory pressure to build up workplace charging facilities for their employees. However, the impact of EV charging loads on businesses’ specific electricity consumption profiles remains largely unknown. Our study addresses this challenge by presenting a mathematical optimisation model, available via an open-source web application, that empowers business executives to manage energy consumption effectively, enabling them to assess peak loads, charging costs, and carbon emissions specific to their power profiles and employee needs. Using real-world data from a global car manufacturer in South East England, UK, we demonstrate that smart charging strategies can reduce peak loads by 28% and decrease charging costs and emissions by 9% compared to convenience charging. Our methodology is widely applicable across industries and geographies, offering data-driven insights for planning EV workplace charging infrastructure.

This paper presents results of the prequalification test for ancillary services of a Battery Energy System (BESS) integrated with a Photovoltaic (PV) plant at the same Point of Connection (installed in Denmark. All services for DK2 area have been tested: Frequency Containment R- Normal (FCR-N), Frequency Containment Reserve - Disturbance (FCR-D), Fast Frequency Reserve (FFR), and automatic/manual Frequency Restoration Reserve (a/m FRR). The study details the rigorous testing procedures and performance evaluations conducted to ensure compliance with the requirements outlined in the "Prequalification of Units and Aggregated Portfolios" document. The prequalification tests include a series of assessments such as step and sine response tests, along with Normal Energy Management (NEM) and Alert Energy Management (AEM) strategies. The results demonstrate the BESS's compliance with these requirements, showcasing its ability to provide ancillary services. Furthermore, the study highlights the significant economic profitability of participating in the ancillary service market, emphasizing the substantial financial returns for operators.

As distributed generation becomes more prevalent in the electric power system, it is essential to analyze the generation mix and associated technologies to ensure resilient and stable grid operation. In particular, the increased share of grid-following versus grid-forming generation can pose serious grid stability issues and needs to be carefully evaluated. This study employs the Modelica open-source modelling framework to conduct dynamic simulations on a medium-voltage distribution network model where demand is primarily served by local distributed generation. In order to increase scalability, the complexity of the distribution network model is reduced to an equivalent reduced-order model that preserves the dynamic behavior of the original detailed system. Various penetration scenarios of conventional grid-following converters versus distributed synchronous generators are investigated. The scenarios are examined during sudden load disruptions of varying magnitudes, similar to observed events such as the 2021 Texas power crisis or the 2003 East Coast blackout. The results reveal that, in scenarios with a high penetration of grid-following converters, grid stability is significantly compromised. In particular, penetrations greater than 80\% lead to disconnection of all converters during severe load increases.

With the rising share of renewable energy, grid-forming converters are now key in national grid codes. They emulate voltage source behavior even in weak grids or without traditional synchronous machine support, while also providing inertia and short-circuit current. New grid codes demand that these converters maintain voltage source characteristics, supply instantaneous inertia support, offer robust short-circuit current, and withstand phase jump disturbances.

Technically, the goal is for converters to mimic synchronous generators as closely as possible—a concept originally suggested by “virtual synchronous machine.” However, a major challenge is achieving sufficient overcurrent capability, which requires notable hardware enhancements in two main areas:

1. Power Semiconductor Modules: These must handle large, instantaneous overcurrents and thermal stresses. Solutions include paralleling devices or using higher-specification semiconductors.
2. Filter Inductors and Magnetic Components: These elements need an increased magnetic flux capacity to prevent core saturation and thermal damage during high-current transients.

These upgrades lead to higher costs, larger sizes, and more complex system designs. Insufficient overcurrent capability can jeopardize voltage support during grid disturbances, risk synchronous stability during phase jumps or frequency fluctuations, and limit fault response in short-circuit events—posing challenges for relay protection and fault detection.

Thus, determining the necessary overcurrent capability for grid-forming converters is crucial. This issue affects not only the technical feasibility and safety of converter technology but also equipment investment, operating costs, and the overall reliability and economic efficiency of power systems. Grid operators must ensure stable voltage characteristics, adequate short-circuit current, and synchronism, while converter owners need to balance enhanced overcurrent capability with investment control to benefit from services like inertia support.

To address this issue comprehensively, the paper discusses:

1. Grid Characteristics and Technical Requirements: Analyzing the short-circuit ratio (SCR), the grid impedance X/R ratio, and the diverse overcurrent capability requirements in various national grid codes.
2. Specific Grid Topologies and Fault Scenarios: Examining the challenges posed by instantaneous high currents in typical fault scenarios, such as ground faults.
3. Economic Considerations and Market Returns: Evaluating hardware costs, energy consumption, and maintenance expenses associated with enhancing overcurrent capability, alongside the compensation from providing inertia and rapid frequency response services. This analysis weighs the trade-offs between investment and operating costs.

Driven by the increasing scale of offshore wind farms and the growing need for greater cross-border interconnection capacity, bipolar High Voltage Direct Current (HVDC) systems based on Modular Multilevel Converter (MMC) technology are expected to play a key role in future transmission networks. However, concerns about techno-economic feasibility while relying exclusively on point-to-point links have prompted the industry to tackle the challenges of transitioning to Multi-Terminal (MT) configurations.

In this context, the InterOPERA project was launched to enable future HVDC systems from different suppliers to operate together, paving the way for the actual implementation of Europe’s first MT, Multi-Vendor (MV), multi-purpose HVDC projects. InterOPERA has already made significant contributions, including the development of common functional specifications and minimum interface requirements. In the coming months, a Real-Time (RT) demonstrator will be implemented to validate and refine the proposed methods and processes, ensuring their practical applicability. This work focuses on activities supporting the deployment of the RT demonstrator, particularly on HVDC grid design studies using generic models to provide inputs to the detailed subsystem specifications. Three study packages have been defined:

1. DC load flow (LF)-based contingency analysis ensuring that DC voltage regulation capabilities and continuous operating ranges align with system operation under the selected risk policy.

2. Dynamic studies quantifying temporary excursions of electrical quantities following contingencies, to ensure they remain within equipment limits and do not trigger unwanted protection operations.

3. Transient studies assessing the required withstand capabilities of network assets and grid-connected devices, considering the performance of available protection system.

A series of three papers presents key findings from this work. This first part focuses on steady-state studies, determining secure DC voltage operating ranges and preliminary droop gains to ensure compliance with the N-1 rule. The proposed scenario-based approach was introduced in a previous work and applied to two configurations of a three-terminal HVDC system—with and without offshore wind generation—considering a pole-wise and multi-slope droop control strategy, as well as the presence of DC circuit breakers. The challenges of primary DC voltage control in highly inductive DC grids along with the impact of neutral voltage shifts during asymmetrical operation on pole-to-ground voltages have been highlighted.

Building on these findings, this follow-up work extends the analysis to degraded operating modes, including permanent asset unavailability and changes in the HVDC system grounding location. Additionally, trade-offs between maintaining N-1 compliance and operational losses are highlighted.

Driven by the increasing scale of offshore wind farms and the growing need for greater cross-border interconnection capacity, bipolar High Voltage Direct Current (HVDC) systems based on Modular Multilevel Converter (MMC) technology are expected to play a key role in future transmission networks. However, concerns about techno-economic feasibility while relying exclusively on point-to-point links have prompted the industry to tackle the challenges of transitioning to Multi-Terminal (MT) configurations.

In this context, the InterOPERA project was launched to enable future HVDC systems from different suppliers to operate together, paving the way for the actual implementation of Europe’s first MT, Multi-Vendor (MV), multi-purpose HVDC projects. InterOPERA has already made significant contributions, including the development of common functional specifications and minimum interface requirements. In the coming months, a Real-Time (RT) demonstrator will be implemented to validate and refine the proposed methods and processes, ensuring their practical applicability. This work focuses on activities supporting the deployment of the RT demonstrator, particularly on HVDC grid design studies using generic models to provide inputs to the detailed subsystem specifications. Three study packages have been defined:

1. DC load flow (LF)-based contingency analysis ensuring that DC voltage regulation capabilities and continuous operating ranges align with system operation under the selected risk policy.

2. Dynamic studies quantifying temporary excursions of electrical quantities following contingencies, to ensure they remain within equipment limits and do not trigger unwanted protection operations.

3. Transient studies assessing the required withstand capabilities of network assets and grid-connected devices, considering the performance of available protection system.

A series of three papers presents key findings from this work. This second part focuses on dynamic stresses at the connection points of various subsystems following unit outages, simulated through forced converter blocking, and temporary AC faults. Minimum dynamic operating ranges required to prevent inadvertent protection triggers are ultimately defined, ensuring compliance with the N-1 security criterion.

Specifically, temporary overvoltage and undervoltage profiles are constructed from detailed EMT simulations of selected contingencies applied to the initial operating conditions defined in the steady-state study (N situations). The distinction between HVDC grid design and subsystem control design studies is highlighted, while recognising the influence of dynamic performance on observed stresses. Consequently, classical indicators such as settling times and overshoots are reported alongside the maximum temporary excursions of relevant electrical quantities. Finally, the impact of critical modelling assumptions, including design parameters and control settings, is also analysed.

Driven by the increasing scale of offshore wind farms and the growing need for greater cross-border interconnection capacity, bipolar High Voltage Direct Current (HVDC) systems based on Modular Multilevel Converter (MMC) technology are expected to play a key role in future transmission networks. However, concerns about techno-economic feasibility while relying exclusively on point-to-point links have prompted the industry to tackle the challenges of transitioning to Multi-Terminal (MT) configurations.

In this context, the InterOPERA project was launched to enable future HVDC systems from different suppliers to operate together, paving the way for the actual implementation of Europe’s first MT, Multi-Vendor (MV), multi-purpose HVDC projects. InterOPERA has already made significant contributions, including the development of common functional specifications and minimum interface requirements. In the coming months, a Real-Time (RT) demonstrator will be implemented to validate and refine the proposed methods and processes, ensuring their practical applicability. This work focuses on activities supporting the deployment of the RT demonstrator, particularly on HVDC grid design studies using generic models to provide inputs to the detailed subsystem specifications. Three study packages have been defined:

1. DC load flow (LF)-based contingency analysis ensuring that DC voltage regulation capabilities and continuous operating ranges align with system operation under the selected risk policy.

2. Dynamic studies quantifying temporary excursions of electrical quantities following contingencies, to ensure they remain within equipment limits and do not trigger unwanted protection operations.

3; Transient studies assessing the required withstand capabilities of network assets and grid-connected devices, considering the performance of available protection system.

A series of three papers presents key findings from this work. This third part focuses on transient stresses at the connection points of various subsystems during DC faults, specifically Short-Circuit Currents (SCC) and Temporary Overvoltages (DC-TOV) throughout the fault separation process. Detailed EMT simulations examine pole-to-ground faults along DC cables and at DC switching station (DCSS) busbars, as well as single-phase faults at the transformer’s converter-side.

The impact of critical design parameters is analysed, including DC circuit breaker (DC CB) fault neutralization times, converter current capabilities, DC reactor sizing, and system grounding considerations. The challenges and opportunities of applying the InterOPERA functional framework, as proposed in Deliverable 2.1, are discussed. Finally, insulation coordination aspects are briefly addressed, with preliminary guidelines on defining the dedicated metallic return (DMR) insulation level and setting grid-side surge arrester protective levels.

The increasing integration of renewable energy sources has led to a rise in Power Electronics Interfaced Resources (PEIR), challenging traditional Root Mean Square (RMS) based modelling and stability analysis. Unlike synchronous machines, PEIR display fast dynamics across a wide frequency range, necessitating Electromagnetic Transient (EMT) models to capture high-frequency phenomena. Despite this, RMS models are still widely used to study slow system dynamics, even under high PEIR penetration. This study evaluates the adequacy of RMS models for analyzing slow dynamics in converter-dominated systems, focusing on Grid-Following (GFL) control schemes. A generic GFL converter is modeled in EMT and simplified to RMS. State-space analysis reveals that current control, a fast control loop often simplified in RMS models, affects slow modes, challenging the assumption that RMS models accurately capture slow dynamics. Comparative EMT and RMS simulations confirm these initial findings, underscoring the limitations of RMS models and the importance of considering fast control dynamics, even in slow timescale studies.

European Transmission System Operators (TSOs) face a surge in battery connection requests, and some have introduced hosting capacity maps to guide project developers toward optimal grid integration areas.

This paper presents a novel concept called joint hosting capacities, which maximises the total hosting capacity for batteries, no matter how many are connected and whatever their simultaneous injection. Additionally, joint hosting capacities are defined for any maximum number of limitations (or curtailment) imposed to plants because of network congestions. Since any combination of setpoints is allowed within hosting capacities, this approach ensures robustness to changes in business models over years by battery operators. Hence, joint hosting capacities are expected to reflect the actual transfer margins of the grid in a more accurate way than existing capacity maps.

The mathematical description of the approach is presented as an optimisation problem, which is intractable for real-world networks. Therefore, an efficient algorithm is exhibited to overcome this limitation. Although it delivers slightly suboptimal capacities, these are valid with respect to network thermal limits and the maximal number of batteries limitations that was initially selected. Finally, the feasibility and effectiveness are validated on a representative network, specifically the French 400 kV network.

Tamil Nadu, a pioneer in India’s renewable energy transition, is proactively deploying innovative strategies to seamlessly integrate its high penetration of wind and solar energy into its grid, while adapting to evolving operational and regulatory landscapes. The challenges are magnified under the open access regime, where diverse, decentralized generators require accurate, transparent and timely data exchange for metering, scheduling and energy settlement. In response, the Tamil Nadu Generation and Distribution Corporation executed India’s first large-scale commercial-scale Automatic Meter Reading system for renewable energy generators operating under the open access regime.

This paper presents a comprehensive account of the technical design, implementation strategy and regulatory implications of the AMR system. Prior to deployment, energy accounting relied heavily on manual meter reading and paper-based communication, which led to inconsistencies, delays in billing and frequent disputes between the utility and generators. The AMR solution, built around GSM/GPRS-enabled digital meters, centralized data concentrators and remote monitoring infrastructure, enables real-time data acquisition and secure communication to centralized databases.

A key highlight of the system is its integration of Time-of-Day metering functionality. This feature allows for differential recording of energy generation across peak, off-peak and normal hours, aligning renewable energy injection data with tariff structures mandated by the Tamil Nadu Electricity Regulatory Commission. The inclusion of ToD capability enhances both operational and commercial efficiency, enabling accurate forecasting, load management and time-sensitive energy settlement practices.

The paper further explores how the AMR system aligns with statutory open access provisions and supports operational transparency and fairness in energy accounting. Its successful deployment has led to a significant reduction in billing errors, enhanced the integrity of the scheduling process and streamlined the settlement mechanism. The automation of energy data management has minimized human intervention, improved generator trust and facilitated regulatory compliance with open access energy injection protocols.

Furthermore, the AMR infrastructure lays the foundation for future functionalities, including predictive scheduling, flexible generation dispatch and integration with demand-side management platforms. The granular metering data enables accurate forecasting and supports energy balancing strategies, potentially facilitating participation in ancillary services and real-time energy markets. This foresight positions the system not only as a current operational tool but as an enabling layer for future smart grid services.

Tamil Nadu’s AMR initiative stands as a scalable and replicable benchmark for emerging economies and regions with weak grid infrastructure, particularly those navigating the complexities of liberalized electricity markets. This facilitates accurate tracking of energy injections during peak, off-peak and normal hours, promoting efficient energy use and market-based incentives. By effectively bridging the gap between technological capability and regulatory compliance, the project underscores the pivotal role of digital metering infrastructure in enabling transparent, reliable and sustainable large-scale renewable energy integration.

Grid-forming battery energy storage systems (GFM-BESS) are crucial for enhancing grid stability and enabling black start capabilities. This study examines the black start performance and fault response of a GFM-BESS within a Wind-BESS hybrid power plant through multi-scenario field tests. The first phase validates the soft start-up capability on a 35kV bus, achieving voltage buildup within 10 seconds, with steady-state voltage maintained at 1.06–1.08 p.u. and frequency deviation within ±0.2 Hz. The second phase demonstrates plant-level black start and load operation, where the GFM-BESS sustains bus voltage between 0.9–1.0 p.u., with transient peaks under 1.35 p.u. during transformer switching or line energization, and transient durations below 7 ms. The third phase involves a three-phase short-circuit test: during a 250-ms fault, terminal voltage drops to 0.3 p.u. with a peak fault current of 2.97 p.u., followed by rapid recovery. Results confirm the exceptional voltage and frequency regulation, transient stability, and fault resilience of GFM-BESS, providing vital insights for improving grid reliability in systems with high inverter-based resource penetration.

With the growing integration of Renewable Energy Sources (RES) and High-Voltage Direct Current (HVDC) lines, maintaining grid stability has become increasingly complex. RES, being non-programmable, introduces fluctuations in voltage and frequency, while HVDC lines affect grid dynamics. Synchronous Condensers (SynConds) offer a robust, reliable and cost-effective solution by providing reactive power, voltage regulation, short-circuit power, and inertia. Built from standard turbogenerators and remotely controlled, SynConds deliver rapid dynamic response and can include flywheels to boost inertia with minimal energy and noise impact. Ansaldo Energia has been a pioneer in this field, starting with its first SynCond plant at Terna’s Codrongianos substation in Sardinia in 2014. Since then, it has developed multiple plants across Italy, particularly in Central and Southern regions where RES penetration is highest. The company also repurposes components from decommissioned coal and gas plants to create new SynConds, exemplified by a recent project in Southern Italy. As grid codes and market structures evolve, hybrid systems combining RES and thermal generation with SynCond capabilities offer new opportunities for grid balancing services. With global energy systems shifting toward renewables, the demand for SynConds is set to rise, ensuring reliable and stable power networks for the future.

Transmission system operators (TSOs) increasingly encounter small-signal instabilities (SSIs) when integrating converter-based resources into modern, converter-dominated power systems. Identifying and mitigating such instabilities is challenging due to complex converter interactions among multiple converters under a wide range of operating points (OPs). The challenge is particularly critical during the grid-connection process, where TSOs must validate stability before new converter-based resources are integrated into the system. Intellectual property rights (IPRs) further complicate the analysis by restricting TSOs' access to original equipment manufacturers (OEMs) and plant owners (POs) detailed models, which pose difficulty in coordinating studies and communicating analysis insights among multiple parties. Hence, methods that can address both the inherent complexity of SSIs and the IPR restrictions are needed. To address this challenge, this paper proposes a collaborative study framework between the TSO and OEMs/POs, which preserves OEM/PO IPRs while enabling an automated system-level small-signal stability risk assessment and root cause identification across the OP space. The framework considers black-box OEM/PO state-space models, which are combined with the TSO’s power system model using the component-connection method, enabling the eigenvalue-based stability analysis. The effectiveness of the study framework is demonstrated on a system with two grid-following wind-power plants (WPPs) and two parallel grid-forming high-voltage direct-current interconnections, where one WPP is undergoing grid-connection. Electromagnetic transient simulations validate the theoretical analysis of the framework.

There is ongoing discussion worldwide on the production of green hydrogen at scale within hydrogen hubs which integrate renewable energy resources (RES) and large-scale hydrogen electrolysis technologies within microgrids, co-located with hydrogen storage, distribution, end-use processes. One of the key challenges in development of hydrogen hubs relates to maintaining their grid stability and balancing with variable RES. To reduce capital costs associated with additional grid enhancing technologies such as batteries and synchronous condensers, there is a discussion on leveraging electrolyzer flexibility to enhance microgrid stability and minimize renewable energy curtailment. In the context of this work, flexible operation of electrolyzer refers to adjustment of its active and reactive power to contribute to microgrid voltage/frequency stability, also managing renewable energy output. This work aims to highlight the potential electrochemical and operational challenges that may limit the flexible operation of electrolysis plants and their participation in system support services, such as stack degradation, reduction in hydrogen production efficiency, stack ramp rate limit, stack partial loading constraint, and the challenges in no-load operation of electrolysis stack. Additionally, we clarify various operational constraints imposed by the downstream hydrogen storage/process that may limit frequency control from electrolyzers. Our comprehensive analysis seeks to provide practical recommendations on electrolyzer utilization for system support services, ultimately adding certainty to design and development of hydrogen projects.

Decarbonizing the European Union’s (EU) road freight sector will require a significant share of zero-emission trucks (ZET), covering a wide spectrum of trucking applications, from last-mile delivery to long-haul cross-border heavy trucks. In 2024, over 14,000 ZETs were registered, of which 3,400 were heavy trucks with gross vehicle weight (GVW) above 12 tonnes, representing 1.2% of heavy truck sales. Light- and medium-duty trucks below 12 tonnes recorded a 10% ZET market share in 2024, a significant increase from the 6% shares in 2023 (Mulholland & Ragon, 2025). This increase in ZETs sales has been mainly driven by the EU heavy-duty vehicles (HDVs) CO2 standards Regulation (EU) 2024/1610, where the last review of the regulation – conducted in May 2024 - mandates a 45% reduction in CO2 emissions relative to 2019, a target truck manufacturers can only reach by ramping up their sales of ZETs.

Battery-electric trucks (BET) are expected to dominate the sales of ZETs due to their technology maturity and superior economic performance. The expected BET fleet will require an extensive charging infrastructure network to cover the fleet’s energy needs. To this end, the EU issued Regulation (EU) 2023/1804, referred to as the Alternative Fuels Infrastructure Regulation (AFIR), to ensure minimum infrastructure support for alternative fuel vehicles. The AFIR is expected to be reviewed before the end of 2026, providing an opportunity to assess if the charging infrastructure targets are enough to accommodate the expected BET fleet by 2030.

This study estimates the needed charging infrastructure by 2030. The methodology is mainly composed of two main parts: (1) truck fleet sales and stocks analysis where the total annual sales and stocks of electric trucks are calculated, and (2) truck charging infrastructure needs assessment based on the energy needs, the charging infrastructure needs are estimated considering truck charging patterns and infrastructure utilization. By 2030, the analysis shows that more than 330,000 battery-electric trucks will be running on the European road network, distributed over light, medium, and heavy-duty trucks. Given this BET stock, close to 70,000 public chargers will be needed to cover the fleet energy and power needs, out of which 4,000 are MegaWatt chargers, 9,000 are fast DC chargers at 350 kW, and the rest are overnight chargers around 50 - 100 kW. In addition, the analysis shows that based on truck traffic data, some European countries like Germany, Poland, and Belgium are expected to host close to 40% of those chargers.

The analysis serves to inform experts and policymakers about the charging needs for battery-electric trucks in the EU, given the differences between European countries.

The electrical interface systems currently used for external power supply to railway vehicles are primarily based on the UIC 552 and UIC 554 standards developed in the 1970s. These standards address only the transfer of electrical energy and no longer meet the demands of modern railway applications. Their limitations include manual meter readings that hinder efficient billing, reliance on physical identification tokens considered impractical by users, the absence of automated load management during peak demand, and the lack of support for vehicle-to-grid energy feedback. To address these challenges, this paper examines the potential application of road vehicle charging standards—specifically ISO 15118—to railway applications. The proposed approach begins with theoretical analyses of existing railway infrastructure, evaluating its compatibility with digital charging protocols and identifying technical barriers and necessary adjustments. Railway-specific requirements are taken into account. In addition, the study considers emerging developments, including bidirectional charging, the evolution of the Open Charge Point Protocol, and the applicability of DIN EN 50546 for three-phase power supply at 63/125 A and 600 A. Furthermore, a power supply via the train line according to UIC 554 is evaluated. This investigation presents an implementation concept for ISO 15118 in railway applications, aiming to modernize railway external power supply systems and enhance efficiency, flexibility, and interoperability.

As an emerging renewable energy technology, offshore wind harnesses superior and steadier wind resources, enabling the implementation of large-scale projects exceeding gigawatt capacities. This rapid expansion pushes offshore wind power plants (OWPPs) further from shore. High voltage direct current (HVDC) has emerged as a key technology for connecting OWPPs due to its high efficiency in transmitting electrical energy over long distances. As a result of the ongoing energy transition, HVDC-connected OWPPs are increasingly being operated with grid-forming (GFM) control strategies, replacing the previously employed grid-following (GFL) control approaches. This shift enables the HVDC-link and the OWPPs to contribute to system stability by providing ancillary services to the grid.

A sensitivity analysis is conducted to evaluate the impact of the GFM HVDC control on the dynamic behavior of GFM offshore wind turbines. A symmetrical monopole HVDC link with Modular Multilevel Converters (MMCs) connects the offshore wind farm. The GFM control concept is giving rise to a fundamentally different behavior of the renewable energy sources. A voltage-sensitive GFM control scheme replaces the ideally voltage-independent GFL control schemes. Therefore, the number of grid disturbances per year, affecting the lifetime of the components of the renewable energy sources, might rise.

First, the investigated system is introduced. Subsequently, the operational strategy for propagating onshore grid events to offshore wind turbines is outlined. The wind turbines are modeled using both an electrical and a mechanical model. The mechanical model incorporates a single-mass drivetrain model. However, the wind turbines' modeling is not within this paper's scope. All grid-side converters in the system have implemented a GFM control. The sensitivity analysis performed in this paper's investigation focuses on HVDC control. A variation in the GFM onshore HVDC converter control and the overall energy control is carried out. The overall energy control influences the amount of disturbances directly transferred to the offshore HVDC converter station as proposed by the "OffWiPP" operational strategy. Different onshore grid events, e.g., voltage phase angle jumps and Rate of Change of Frequency (RoCoF) events, are used to emphasize the provided phase step or RoCoF power and the provided energy from the MMC's and the wind turbines.

The performed investigations show how a variation in the HVDC control can distribute the energy supplied to the grid disturbance between the HVDC and the energy stored in the rotational mass of the wind turbines. The steepness of the onshore grid event, transferred to the offshore grid, influences the mechanical system of the wind turbines. Consequently, a higher contribution of the HVDC to the onshore grid event reduces the steepness of the event seen by the offshore wind turbines.

With the large-scale integration of renewable energy sources, modern energy systems are progressively transitioning towards green and low-carbon paradigms. However, the inherent volatility and intermittency of renewable energy have introduced significant technical challenges to the safety and stability of power systems following high-penetration renewable integration. Consequently, the industry has adopted advanced technologies such as grid-forming control to ensure stable operation of future power systems with ultra-high renewable energy shares.

This presentation will systematically analyze the evolutionary trajectory of grid-forming technology and its engineering practices in addressing stability issues associated with large-scale renewable energy integration within next-generation power systems.

This paper explores the application of Grid-Forming Battery Energy Storage Systems (GFM-BESS) to enhance power system stability in the large-scale system-wise simulations, using a real-world incident in Denmark’s eastern transmission system (DK2). On August 6, 2020, DK2 experienced a series of faults in transmission lines, which led to a drastic reduction in short-circuit strength, the disconnection of key assets (HVDCs, Synchronous condensers), and a potential risk of system collapse. This event exposed the vulnerability of conventional stability resources like synchronous condensers (SynCons) under weak grid conditions and highlighted the growing need for faster, more flexible grid support solutions in systems with high share of converter-based facilities.

To evaluate the potential benefits of GFM-BESS in such critical scenarios, Electro-Magnetic Transient (EMT) simulations were conducted in the system-level using vendor-specific models to retrieve real-world situations. The incident was replicated in detail, capturing system topology, operational states, and the fault sequence. Two system configurations were compared: the original setup with existing SynCons and a modified version with a GFM-BESS replacement. Furthermore, the study evaluated the effects of different GFM-BESS capacities, installation sites, and adjustments to control parameters to gain insights into effective deployment strategies.

Results show that the GFM-BESS not only stabilizes voltage and damps oscillations more effectively than SynCon but also enhances system resilience with a smaller capacity than SynCon. Voltage profiles recover within seconds after disturbances, and active/reactive power swings are significantly reduced with support from GFM-BESS. The nearly instantaneous and inherent reactive power response of the GFM-BESS plays a critical role in this rapid stabilization. Further simulations confirm that the location of the GFM-BESS installation can have a major influence on system response, with optimal placement delivering better performance on oscillation damping and fault recovery. Increasing the converter capacity of the GFM-BESS further enhances performance, while tuning its control parameters optimizes the balance between responsiveness and stability.

These findings demonstrate that GFM-BESS is superior to SynCon for enhancing system stability with high share of converter-based facilities. Compared to traditional synchronous condensers, GFM-BESS solutions offer rapid and inherent response and thus better voltage support, while being more adaptable to future grid challenges. From a system operator’s perspective, strategic deployment of GFM-BESS can provide an effective approach of future-proofing the grid while enabling a secure and reliable transition to a converter-dominated power system. The study suggests incorporating GFM technology into upcoming grid planning and investment frameworks, particularly in areas where maintaining stability with conventional solutions is less practical.

Dynamic Link Library (DLL) applications are a powerful approach for modelling of as-built functionality of the vendor-specific equipment and control systems to be shared with the clients without divulging strictly privileged information, intellectual property or know-how of the vendors.

The clear advantage of the approach is that the vendor can convert complete and sufficient models of the equipment and control systems from a preferred by the vendor simulation software, such as C++, into the DLL applications to be used with the client’s simulation software, such as the DIgSILENT PowerFactory®, for dynamic stability assessment of the electric power grids. Though the electro-magnetic transient (EMT) modelling can be included into the DLL applications and used for the RMS assessment of large power grids including symmetrical and asymmetrical short-circuits and island operations with a passive network without compromising the execution time.

Among pronounced challenges of the DLL applications can be: (i) – difficulty to perform fully variable time-step simulations, i.e., automatic adaption of the time step within 1 to 10 ms, (ii) – appearance of numerical discontinuities about the simulation events, i.e., so-called numerical spikes having noticeable magnitudes in voltage and reactive power at abrupt voltage changes following application or clearance of short-circuits. The numerical spikes are not present in measurements. Furthermore, the numerical spikes may affect the own control models and propagate to the control models of other equipment models distorting the system-level simulation results.

This presentation describes a method developed by Siemens Gamesa Renewable Energy (SGRE) for overcoming the mentioned challenges of the DLL applications. Using simple and understandable validation cases, the developed method will be demonstrated for an EMT level modelling of a generator in the RMS simulations using the DIgSILENT PowerFactory® software.

The developed method enables numerically robust application of fully variable time-step simulations, such as within a commonly required range from 1 to 10 ms. The developed method efficiently suppresses numerical spikes that would appear at abruptly voltage changes, such as after clearance of short-circuits and allows simulations in an island regime with a passive network.

Recently, the lithium-ion batteries (LIBs) industry has become more expensive due to the limited resources and the uneven global distribution of lithium, with its rising prices. Therefore, sodium-ion batteries (SIBs) are promising as an attractive replacement to LIBs for storing energy because of the abundance of sodium resources. Additionally, demand for natural graphite in the battery industry has increased dramatically despite its limited reserves; this requires finding new materials and methods to provide alternatives for the graphite. Whereas coal is a high-quality, widespread carbon source, it consists of graphitic crystalline domains connected with amorphous carbons that the graphitization process can further transform into synthetic graphite. The flash Joule heating (FJH) method is considered a time- and energy-saving, strong candidate for a traditional graphitization method. The cost to transform 1 ton of amorphous carbon into graphene using FJH ranges from $30 to $161, depending on the starting source. In contrast, the cost of synthetic graphite is approximately 13 USD/kg, and for natural graphite, it is approximately 8 USD/kg. As an emerging synthetic method, FJH exhibits great superiority in environmental friendliness and low time and energy consumption, making it promising in transforming coals into graphitic carbon materials. Based on these considerations, porous graphitized coal anode materials for SIBs were prepared using a two-step process involving catalytic activation using nickel chloride, iron chloride, and zinc chloride catalysts, followed by high-temperature graphitization using flash Joule heating. XRD, Raman spectroscopy, SEM, TEM, and BET analyses confirmed the coal sample (FHC) transformation from an amorphous to a crystalline structure, with expanded interlayer spacing, increased porosity, and reduced defects. These structural features significantly enhance sodium storage capacity and electrical conductivity. The electrode of the FHC sample, prepared via flash Joule heating, showed higher initial charge and discharge capacities of 298.9 and 642.7 mAh/g at 0.1 C. The superior specific capacity of FHC can be attributed to its improved crystallinity and enhanced porosity resulting from high-temperature catalytic graphitization. The FHC electrode demonstrated outstanding cycling stability, with a capacity retention of 99% after 100 cycles at 2C, confirming the effectiveness of this graphitized coal material for high-performance SIB applications.

Therefore, the low price of coal and its abundant reserves, combined with the FJH technology, can be exploited to produce high-quality graphitic coal for use as anode materials for SIBs.

Following an episode of enthusiasm surrounding the opportunities of green hydrogen to achieve European emission reduction goals and reduce dependence on energy imports, the implementation gap between announced and realised projects mirrors the slowed ramp-up of European green hydrogen production in recent years. The reasons are high and uncertain production and supply cost compared to hydrogen from alternative sources and a limited and uncertain green hydrogen off-take. Both impair the profitability of green hydrogen production and thus hamper a European ramp-up, necessitating high project subsidies to mitigate business risk for green hydrogen projects. As the European regulatory framework requires the primary usage of renewable power via power purchase agreements (PPAs) for green hydrogen production in most European countries and bidding zones, an additional business risk emerges as soon as power sourcing is due.

PPA power sourcing does not only bring the challenge of matching the fluctuating feed-in of renewable energy sources to a relatively flat off-take of big industrial hydrogen consumers. In addition, the exclusive reliance on mainly long-term PPA contracts brings power supply risks due to the inter-year uncertainties regarding weather-reliant PPA power availability. This applies above all as long as short-term PPA contracts are not available and short-term power purchase via the electricity market for compensation is no option, as it is in the case of green hydrogen production. Here, the PPA or the electrolyser operator must bear the risk.

In this work, we show to what extent green hydrogen production cost is affected by inter-year uncertainties of PPA power availability. Furthermore, we quantify possible hydrogen production cost increases when ignoring those uncertainties in the sizing and operation planning of green hydrogen production systems. To solve this issue, we present an optimisation approach to find a robust PPA, electrolyser and hydrogen storage design, considering the inter-year uncertainties. In addition, the effect of different regulatory adjustments on the financial risk of PPA power sourcing for green hydrogen production are evaluated.

The methodological base for our analyses is a linear optimisation model, minimising the installation and operation cost of a hydrogen production system to meet a predefined hydrogen demand in different power purchase scenarios and system configurations. In addition, we use an extended version of our optimisation model that allows a robust design optimisation considering the uncertainties regarding inter-year PPA power availability.

Our results show that considering the inter-year uncertainties of PPA power purchase allows mitigating the business risk of green hydrogen production by avoiding fines for failed hydrogen delivery or hydrogen compensation purchases due to underproduction, which however comes at the cost of PPA and storage oversizing. Adapting the regulatory framework for power purchase for green hydrogen production could decrease green hydrogen production cost by lowering the necessity for costly PPA and storage oversizing. However, an increased emission intensity can result, whereby the magnitude of increase depends on the form of regulatory adaption and the geographical location of the hydrogen production system.

Power system oscillations pose a significant threat to power grids, potentially resulting instability and blackouts. Traditional solutions for damping these oscillations include power system stabilizers (PSS) associated with synchronous generators and Flexible AC Transmission Systems (FACTS) devices [1,2]. However, as renewable energy sources replace conventional power plants, the PSS based on synchronous generators is no longer feasible. Consequently, damping power system oscillations in large systems with large share of renewable energy sources becoming a challenging task, e.g. the low-frequency oscillation before the blackout in Spain on 28.April 2025 shown in Fig. 1 [3].

Fig. 1. Virtual synchronous generator control

This paper investigates the influence of grid forming controls, specifically the virtual synchronous generator (VSG), as shown in Fig. 2, on oscillation stability in power systems with high penetration of renewable energy. The study employs modal analysis and time-domain simulations to evaluate the interactions between VSG controllers and synchronous generator controllers. Results reveal that VSGs are participating the inter-area oscillations and could improve overall system stability, even in scenarios where conventional stabilizers are deactivated. The findings underscore the importance of VSGs in ensuring the reliability of modern power systems under the global energy transition.

Fig. 2. Virtual synchronous generator control

The paper applies grid forming controllers to the VSG of the four machine two area power system as shown in Fig. 3 [1,2]. The PSSs are disabled to emphasize the impact of VSG. A 100MW VSG is connected to Bus 6, operating in parallel with synchronous generator G2, resulting in a reduction of G2's active power output to 600MW. This setup allows analyzing the influence of the VSG on power system oscillations. The system structure and power flow results are depicted in Fig. 3. Dynamic simulation results demonstrate their effectiveness in damping power system oscillations in the presence of high renewable energy penetration.

Fig. 3. four-machine two area power system

In conclusion, this paper highlights the potential benefits of using grid forming control for damping oscillations in large power systems and its possibility for improving the system stability.

References

[1] P. Kundur, Power System Stability and Control, McGraw-Hill Education Ltd, ISBN-10:‎ 007035958X.

[2] G. Rogers, Power System Oscillations, Springer, 978-1-4615-4561-3.

[3] https://www.linkedin.com/posts/philippe-jacquod-76227a5_time-will-tell-what-circumstance-or-chain-activity-7322729833828945920-HS44/

The emerging of Direct Current (DC) technologies offers a great opportunity for modernizing and developing of DC power distribution systems, including DC microgrids. When compared with the classical AC systems, the DC networks are considered more efficient, eliminating the reactive power and frequency control and synchronization problems. Despite the numerous review papers published on Low Voltage DC microgrid, a few papers have given sufficient emphasis on Medium Voltage DC microgrid. This review paper discusses the key opportunities associated with the deployment and utilization of MV DC microgrids and advanced DC technologies. Additionally, it examines the potential for integrating renewable energy sources and battery energy storage systems within MV DC microgrids, promoting sustainable and resilient energy solutions. However, the implementation of MV DC microgrids also presents several challenges, such as standardization and regulatory issues, high initial costs, technical complexity, grid integration difficulties, maintenance, power quality issues, and safety risks. This review paper will help readers to understand the present state of development on MV DC microgrid

Due to the rapid increase in residential PV capacity, it gets more and more difficult for the grid to absorb power at peak hours due to overvoltage issues, causing concerns to DSOs and prosumers who are temporarily unable to inject power into the grid.

In collaboration with Belgian DSOs and via the use of metered consumption and injection data, dedicated Monte-Carlo analyses were performed to investigate mitigation measures, among which the PQ control of residential inverters.

The principle of this mitigation measure is to apply a dedicated control to the inverters since they can control their active and reactive power output at will. By either reducing their active power output or absorbing some reactive power in parallel of the active power production, the voltage level can be reduced and inverter tripping due to overvoltages can be avoided.

Several types of PQ controls are possible and have been investigated in this study:

- Constant cos(phi) : absorbing reactive power in parallel of the active power injected, following a constant cos(phi) whatever the active power level;

- Cos(phi) = f(P) : the cos(phi) depends on the active power output (typically, cos(phi) = 1 for low active power level and linearly decreases starting from 50% P);

- Droop control active power P = P(U) : reduce the active power output following a droop curve based on the voltage level measured locally;

- Droop control active power Q = Q(U) : absorb reactive power following a droop curve based on the voltage level measured locally;

- Droop controls active and reactive power in parallel : Q(U) with P(U) as backup if the action of Q(U) is not sufficient to reduce the voltage

Even though only some countries already have a clearly defined regulatory framework for such use of residential PV inverters, it is worthy to analyze the potential benefits of these controls.

In order to analyze and compare the relative efficiencies of the different controls, a dedicated parametrized LV feeder model was developed in Matlab Simulink and Monte-Carlo simulations were performed, with variations of different input parameters and randomly assigned prosumer profiles, based on existing DSO datasets. To account for the disconnection occurrences and corresponding production losses, the inverters’ dynamic behavior was also modelled, down to a time resolution of 10 seconds. The disconnection and reconnection of the inverters were thus accurately modelled and their impact on the production losses accounted for.

Thanks to hundreds of scenarios simulated, statistical insights could be obtained on the efficiencies of the different control strategies, with respect to different KPI’s of interest for the DSOs:

- Global production losses;

- Equity among prosumers;

- Global reactive power flow;

- Impact on the maximum current in the feeder (cf. ampacity).

The rising prevalence of flexible energy resources like electric vehicle chargers and heat pumps adds complexity to distribution grid operations. Concurrently, enhanced observability and controllability through advanced control systems offer ways to address these challenges. While automated systems manage routine operations, outlier scenarios with uncertainty or incomplete data require manual intervention.

This work introduces a concept for a decision support system designed to improve transparency and provide actionable recommendations, enabling operators to resolve incidents - non-routine situations beyond automated handling - efficiently and cost-effectively. Drawing from the DISEGO project and regulatory contexts such as the German §14a EnWG, the decision support system identifies critical issues, classifies incident types (e.g., communication failures, insufficient data), and suggests tailored actions.

The decision support system maps incidents to Smart Grid Architecture Model interoperability layers, ensuring both technical and organizational decision-making aspects are considered. It incorporates real-time data, forecasts, grid models, and regulatory constraints. Key functionalities include incident identification, real-time visualization, uncertainty overlays, prioritized action lists, and system diagnostics, all aimed at supporting operator decisions.

Scenario-based evaluation shows that structured decision support reduces operator workload, enhances grid stability, and accelerates responses during critical incidents, bolstering operational resilience.

This paper details the integration of a large-scale Grid-Forming Battery Energy Storage System (GFM-BESS) – the Darwin-Katherine BESS (DKBESS) - into the Northern Territory's Darwin-Katherine Network (DKN). The project represents the first deployment of grid-forming technology in the Northern Territory (NT) at this scale, with a 35 MVA (45.6 MW overload) facility replacing a retiring synchronous generator at Channel Island Power Station. The BESS provides critical ancillary services including voltage and reactive power control, frequency control ancillary services (FCAS), inertia and system strength.

The integration process required extensive modelling in both RMS and EMT domains and presented unique complexities due to limitations of the existing Network Technical Code. This led to negotiated performance standards and the development of novel control strategies, including Virtual Feeders, a new On-Load Tap Changer (OLTC) control method, and tuned Rate-of-Change-of-Frequency (ROCOF) relay logic.

The paper provides insights into the technical pathways, modelling approaches, and the practical realities of connecting the DKBESS as a crucial pilot for grid-forming technologies in the NT, enabling the integration of IBRs and operation under low system loads by providing essential synchronous-like services. The project is undergoing its final commissioning and compliance testing in Q3 2025. The outcomes are expected to establish a precedent for future grid-forming connections in the NT and provide valuable lessons for larger interconnected grids transitioning to higher levels of renewable generation.

Electric vehicle (EV) smart charging is becoming increasingly important in supporting the electricity grid through frequency regulation services and facilitating the shift to renewable energy. However, EV availability and energy forecasting has emerged as a new field of research, yet it is not fully evaluated in combination with electricity markets. Therefore, this study aims to explore the economic potential of EV availability and energy forecasts when EVs participate in the spot and frequency markets. The method takes into consideration the settlement stage in both markets: frequency containment reserve (FCR) and the spot market. The model is composed of vehicle-to-grid (V2G) optimization for a workplace charging station using an individual EV smart charging model, which optimizes one vehicle. The inputs are historical electricity market and frequency data, while the output is the total electricity cost calculated for a German case study.

The results show that an accurate forecast for availability is crucial for EV smart charging. The availability forecast error contributes to higher penalties from FCR, with larger penalties experienced during summer months. A sensitivity analysis explores the underestimation of the energy content of the EV. This case shows that underestimating the charging session energy need by 50% is equivalent to a completely failed availability forecast. Additionally, an error in the energy content forecast could result in a rise in imbalance settlement costs, which are more prominent during winter months. For a future case study, the simulation could evaluate combining both the energy content and the availability forecast errors with real-world EV data and applying the optimization to multiple chargers.

Greater stress is exerted on the local electricity grid as more sectors are electrified, including transportation, in which passenger cars represent a significant share, and as electricity production becomes increasingly decentralized in terms of solar and wind power. A key challenge for the distribution grid is to connect new production and demand (e.g., large-scale home charging of electric vehicles, EV) in both space and time. While several studies have examined how hourly electricity prices affect EV charging behavior, less attention has been given to the role of network tariffs, fees paid for the use of transmission and distribution grids, in shaping EV charging patterns. Therefore, this study investigates how different network tariff designs influence both the cost-optimal charging of EVs and household peak power demand. Logged EV charging data and hourly electricity spot prices are used as input to a linear cost-minimization model that compares EV charging in three different scenarios, with and without power tariffs. The results show that the network tariff influences when it is cost-optimal to charge EVs, indicating that tariff design could play a critical role in aligning EV charging with grid capacity.

This paper examines the effectiveness of different forecasting tools for local renewable energy production, focusing on the central question: Can LSTM be used for local weather and energy forecasts and how does it compare to commercial weather forecasts?

Research question

The key to a reliable prediction of available renewable energy is a good weather forecast that includes temperature, wind speed, and solar radiation. Such forecasts that include all of these data are commercially available, such as Solcast or Meteoblue. To minimize ongoing costs, a different approach could be the usage of locally gathered data and predict the energy output with AI models. Local weather stations can improve prediction accuracy, as shown in papers by Beinert and Koutensky.

Furthermore, Wöhrle proved that it is possible to use LSTM models to provide an energy forecast up to seven days ahead on a nationwide scale. In Wöhrles’ paper the prediction scale was all Germany and the average of all german wind turbines is considered.

This paper determines whether this is also possible on a local scale and compares the results with those from commercial and satellite-based forecasts. The paper focuses on wind and solar energy as key contributors to localized sustainable energy generation that supports industrial production.

Methology

To use LSTM, local historical weather data is needed to train the model. This data was acquired in a case study by the authors with two local weather stations. As the completeness of the training data set is crucial for LSTM models, the NaN values that occur are filled with data from the nearest DWD weather station. In total, four different datasets were used:

• Self acquired data consisting weather data and the real production data from the PV-system of a local company

• Self acquired data from the roof of a building of UAS Dortmund including weather data and the output from a small wind turbine

• Weather data from DWD to complete the self acquired datasets

• Commercial weather forecast from meteoblue.com

The paper compares the predictive accuracy of LSTM models trained on historical and local data with that of conventional weather forecasts, separately, for both solar and wind scenarios.

his research is highly relevant to sustainable production, offering insights into how localized forecasting can enhance energy autonomy in industrial settings and reduce losses due to energy distribution. Preliminary results indicate that machine learning-based approaches, particularly LSTM models, hold significant promise for improving the accuracy of site-specific energy forecasts.

The recently published VDE note “Technical requirements for grid-forming properties including the provision of instantaneous reserve”, specifies which requirements gridforming units have to fulfill in Germany and how these capabilities are proven. The verification process consists of several steps which include measurements as well as simulations with a validated simulation model. This paper summarizes the requirements and highlights the most important steps that manufacturers should take now.

Electromagnetic-transient (EMT) as well as Dynamic-Phasor (DP) simulations of power system stability events using Modified Nodal Analysis (MNA) need repeated factorization of large sparse matrices whenever topology changes occur—such as short circuit faults, line protection tripping and voltage induced tripping of generators or loads. Traditional approaches rebuild the full system matrix at each event or precompute and factorize system matrices based on anticipated switching events.

In this paper we propose a network tearing (diakoptics) approach that partitions the system into subnetworks, recomputing only the MNA blocks associated with topology changes. Previous studies have already shown that parallelizing simulation steps within the diakoptics framework can significantly improve performance. In this work, we show that diakoptics offers performance benefits even without parallelization, as only the matrix blocks affected need to be refactorized for topology changes. We validate our approach against full-system MNA solutions for both EMT and DP simulations and present results quantifying performance improvements and scalability across different network sizes and partitioning granularities.

Wind energy is projected to become a leading source of electricity worldwide, driving rapid expansion in wind turbine (WT) deployment onshore and offshore. Ensuring compliance with evolving grid codes is essential for successful operation of these turbines. Traditional field-based testing is constrained by site conditions, lengthy timelines, and specialized equipment, while the increasing scale and complexity of turbines make them costly and, in some cases, technically unfeasible. At the same time, new grid-forming requirements demand advanced WT capabilities—including inertial response, fault ride-through and islanded operation—that are difficult to demonstrate in the field.

This paper presents a co-simulation-based Controller Hardware-in-the-Loop (CHiL) approach for verification of grid-forming capabilities of WTs. Designed to complement field measurements, the test enables verification of advanced grid-forming capabilities that are otherwise impractical to test on site. Aerodynamic and mechanical subsystems are modeled in DNV Bladed®, while the permanent magnet synchronous generator, converter, and grid are simulated in real time. Actual turbine and converter controllers are integrated as hardware replicas. The testbed enables realistic assessment of electromechanical interactions under grid disturbances and supports validation of inertial support and other advanced services. Results demonstrate a practical path to reduce testing time and cost while accelerating deployment of grid-forming WTs.

Offshore wind power generation has received much attention as a key technology for further implementing renewable energy sources to realise carbon neutrality by 2050. Offshore wind farms offer the advantage of large-scale deployment potential. However, since the offshore wind farms are located far from demand centers in most cases, a proper transmission method should be selected for long-distance high-power transmission.

Unlike AC transmission, HVDC (high-voltage DC) transmission consumes no reactive power in transmission lines and allows power delivery using cables with lower current ratings. HVDC transmission has an economic advantage, particularly for long-distance transmission. Submarine HVDC systems are a promising option for connecting offshore wind farms with onshore power grids.

While various activities have been conducted on power transmission from offshore wind farms to onshore power grids, a multi-terminal HVDC system effectively transfers power to multiple onshore demand areas.

This paper proposes a control method for sharing offshore wind power fluctuations between onshore terminals in a three-terminal bipole submarine HVDC system. The paper also reports the results of simulations to confirm the proposed control scheme. The amount of power sent from offshore wind farms and the power system stability of the onshore grids were considered in the simulations.

The simulations were conducted with PSCAD V5.0 to verify whether the prescribed reference values properly shared the wind farm power fluctuations. The offshore wind farm was modelled as an equivalent three-phase current source with constant power output. A detailed synchronous generator model, including an excitror controller and governor controller, was connected to each onshore AC grid to examine grid frequency variations.

The initial condition for the simulation assumed the offshore wind farm output power to be 500 MW. The received power references were 50 MW for onshore terminal 1 and 450 MW for onshore terminal 2. Then, the offshore wind farm output power was changed to 300 MW. Subsequently, the received power references for onshore terminals were updated to 30 MW and 270 MW, keeping the ratio of power reference for terminal 1 and that for terminal 2.

The simulation results confirmed that the proposed control method properly shared power between the onshore two terminals even when the wind farm output power rapidly changed. The results also showed that the grid frequency was kept within a range of 50 ± 0.2 Hz in the onshore grids 1 and 2.

Future work will involve more detailed modelling of offshore wind farm output characteristics and further validation of power sharing between the onshore two terminals.

Accurate modelling of grid-connected converters is essential for system-level stability analysis in power systems with large penetration of inverter-based resources. This paper applies robust control theory to define a matrix relative error that quantifies the discrepancy between modelled and measured converter impedance. Properties of the matrix relative error and the impact on uncertainty bounds in stability analysis are investigated. The validation approach is demonstrated on a Siemens Gamesa offshore wind turbine converter impedance obtained from an analytical state-space model, an electromagnetic-transient (EMT) simulation and test-rig measurements. The EMT and test-rig converter impedance is estimated empirically using a frequency-scan method applied at a selected operating point. The results show that the model and measured converter impedance match within 10 \% matrix relative error for most frequencies. Derived uncertainty bounds are illustrated through a weak-grid stability study, highlighting the importance of applying robust control techniques to manage model uncertainty.

Environmental and energy issues have become a concern worldwide. Power supply in remote island grids mainly depends on diesel generators, which require expensive fuel transportation from the mainland to the island and cause high CO2 emissions. Implementing renewable energy sources on a large scale on the island may solve its environmental and energy problems. However, renewable energy sources may make it challenging to maintain the power supply-demand balance and suppress grid frequency fluctuations.

A HVDC (high-voltage DC transmission) system connecting the mainland and the remote island is considered to solve these power supply-demand imbalance and frequency variation problems. The HVDC system is more economical than AC transmission for long-distance submarine cable transmission. The HVDC system has two converter terminals and a DC cable, allowing bidirectional power flow. When the renewable energy sources have a low power supply, power is sent from the mainland to the island. On the other hand, when the renewable energy sources supply excessive power, power is exported from the island to the mainland.

This paper proposes a control method for the HVDC system connecting the mainland to a remote island with many renewable energy sources. Load variations and fluctuations in the output of renewable energy sources cause a power supply-demand imbalance and frequency fluctuations in the island grid. The proposed control method, in coordination with the synchronous generator, is designed to maintain the power supply-demand balance and suppress frequency fluctuations in the island grid.

The proposed control method was verified by 24-hour-long simulations using Simulink CAD data running on a real-time simulator OPAL-RT (OP4510). The island grid had three types of power sources: a synchronous generator, a solar power plant and a wind power plant. An HVDC system interconnected the mainland and island grids. The synchronous generator was assumed to have a relatively small rated capacity. A sunny and occasionally cloudy weather condition was applied for simulations.

The proposed control method for the HVDC island-side terminal uses a constant-voltage and constant-frequency controller. A droop function between the power and frequency is provided for the controller. The frequency reference value is adjusted based on the power supply-demand imbalance in the island grid, which is measured by an energy management system on the island. This control method coordinates the operation of the HVDC system and synchronous generator to share the required power supply and stabilize the island grid frequency.

The simulation results confirmed that the proposed control method can maintain supply-demand balance and suppress frequency fluctuations for 24 hours, even when the output power of renewable energy sources fluctuates significantly. Thus, the proposed method is an effective solution for installing large-scale renewable energy sources.

Probability density prediction (PDP) of wind power is essential for planned scheduling of generation through coordination with other power sources and limited-capacity storage, and for improving the profitability of wind producers by enabling effective market participation. Ensemble weather forecasts (EWFs) provide valuable information on wind uncertainty, but their computational cost and infrequent updates constrain applicability in intraday decision-making where timely forecasts are required. We propose a PDP framework that dynamically aggregates probability distributions generated by individual EWF members using the continuous ranked probability score (CRPS). Each member first produces its own distribution, and adaptive weights are learned so that the aggregated forecasts best reflect recent observations. To avoid sharpness degradation from naive blending, sparsity regularisation selectively emphasises informative members, resulting in sharper and more accurate forecasts based on a subset of reliable members. By jointly capturing EWF uncertainty and the latest observations, the mechanism enables frequent updates of PDPs even when EWFs are updated only a few times per day. Numerical experiments using real-world data from an operational wind power plant (WPP) show that the proposed approach improves both coverage reliability and sharpness compared with typical methods, including best-member selection and CRPS-inverse weighting, underscoring its potential for practical deployment.

The first bidirectional chargeable electric vehicles are on the market and bidirectional wallboxes are coming soon. This technology enables to also discharge the vehicle's battery storage und use it as flexibility. Because of the ramp up of electrical vehicles this flexibility shows huge potential that needs to be integrated into the ecosystem, market and grid. The use case Vehicle-to-Home (V2H) enables customers to increase their self-sufficiency and make use of dynamic tariffs. Whereas Vehicle-to-Grid (V2G) makes the temporarily stored energy accessible market, grid, or system-oriented. Bidirectional charging not only offers greater flexibility and efficiency in energy consumption, but also actively contributes to optimizing the use of energy when it is most profitable for the customer and the supplier. On top of that this contributes to the development of a sustainable and intelligent energy future, e.g. by increasing the use of green energy. Also, the value potential estimations show a huge monetary benefit for the customer and the supplier of the solution.

The BMWK in Germany brought together nine countries and over 150 people from different industry partners into a so-called coalition of the willing to answer the question:

"What do we still have to do to enable bidirectional charging?"

E.ON was part of this coalition and jointly set the course for what needs to be done to make all systems interoperable with standardized interfaces for several use cases for bidirectional charging. The coalition's main vision is to exchange data fairly and transparently, challenge the current legal framework, identify all hurdles and ultimately create a level playing field for all participants.

In our project BDL Next we work together with a consortium of BMW, Bayernwerk, Compleo, KEO, FfE, Tennet, EBZ, Uni Passau and KIT. (see also www.bdlnext.de)

As the direct successor to the BDL project, we now want to bring bidirectional charging solutions for electric vehicles into mass production. The core of the project is the further development of technical solutions to link vehicles capable of feeding energy back into the grid with established processes in the energy industry for marketing on the energy market or for grid and system support. The three-year project is being funded by the Federal Ministry for Economic Affairs and Climate Protection with over eleven million euros.

E.ON takes over the part of the energy market, energy supply and aggregation/disaggregation of flexibilities especially the battery of the car.

Our presentation will be based on the results of the project BDL Next and of the coalition of the willing.

To address the emerging converter-driven stability challenges in Finland’s increasingly inverter-based power system, Fingrid has developed an ESCR benchmark model for EMT simulations. This model enables evaluation of IBR technologies under weak grid conditions without the confidentiality constraints of wide area EMT models. By replicating multiple instances of the same IBR in a meshed network, the ESCR benchmark model captures dynamic interactions and allows tuning to specific ESCR values.

Simulation results demonstrate that the benchmark model effectively reproduces phenomena observed in wide area EMT studies, including converter driven voltage oscillations and fault ride-through issues. Technologies optimized for weak grid conditions, particularly those compliant with VJV2024 grid code requirements, show improved stability performance. The benchmark model is integrated into Fingrid’s grid connection process at two stages, supporting early validation of technology suitability and later verification of plant-level control stability.

While not a full replacement for wide area EMT simulations, the ESCR benchmark model provides a practical approach for assessing IBR performance, contributing to secure and stable integration of renewable energy into the Finnish grid.

The integration of offshore wind power into modern electricity grids and markets is critically dependent on the accuracy of short-term power forecasts. High-quality forecasts support grid stability, facilitate market participation, and reduce balancing costs. However, generating reliable offshore wind power forecasts remains a significant challenge due to the inherently volatile nature of offshore wind regimes, which are characterized by rapid power ramps and complex meteorological patterns. Additionally, power curtailments caused by grid congestion further complicate the forecasting task by introducing inconsistencies between actual generation potential and observed outputs. This study presents the development and evaluation of advanced offshore wind power forecasting models using machine learning techniques, like gradient boosting methods (XGBoost) and neural network-based approaches (multi-layer perceptrons, MLPs) as well as classical time series methods such as Autoregressive Integrated Moving Average (ARIMA) to assess model generalizability and capture temporal dependencies.

A comprehensive analysis of input features, including numerical weather prediction (NWP) data, production values of past time steps and extrapolated curtailment signals from real wind speed measurements, is conducted to understand their impact on model performance.

The paper addresses methods to pre-process data affected by curtailment and explores techniques to improve the model’s ability to distinguish between physical variability (i.e. windspeed) and grid-induced limitations, such as grid congestions. Through a series of experiments using real-world offshore wind farm data, the study quantifies the forecasting skill of the proposed machine learning models under various scenarios, including high-ramp conditions and periods of curtailment.

Results demonstrate that, with appropriate feature engineering and data treatment, models like XGBoost and MLP can achieve high forecast accuracy, offering a promising approach for operational forecasting in offshore environments. These findings highlight the potential of machine learning, particularly ensemble and neural network models, to enhance the precision and reliability of offshore wind power forecasts—ultimately supporting the secure and efficient integration of offshore wind energy into the power system.

This work was carried out within the Femtec Innovation Lab, a program targeted towards female STEM students to connect them to partners from industry and science. Through interdisciplinary project work this fosters collaborative working with the main focus of increasing the participation and representation of women in STEM fields.

The transition to the electrification of construction vehicles represents a pivotal shift toward greater sustainability in industrial practices. However, it introduces significant challenges to the electrical power grid and local distribution networks, as electrifying these vehicles induces high charging demand. This study assesses the impact of the grid integration of electric construction vehicles in the presence of renewable energy sources (RES), such as solar photovoltaics and wind power. The comparison is made between opportunistic charging and smart charging strategies with optimized local renewable utilization as the objective. The case studies are based on conditions of a city in central Sweden. Multiple seasonal operational scenarios are analyzed. The study evaluates key parameters for system performance, including peak load variations and renewable load matching, quantified by self-consumption and self-sufficiency ratios, as well as their balance. The results show that smart charging strategies can significantly reduce peak load. In the winter week case study, the average net peak load is reduced from 500 kW under opportunistic charging to 85 kW with smart charging. The performance of load matching improves from around 55% with opportunistic charging to around 95% with smart charging. The findings offer practical insights for construction site operators, distribution system operators, and transmission system operators, aiming to support electrification efforts while improving grid stability and sustainability.

This paper introduces a structured framework for integrating probabilistic risk metrics and cost considerations into power system resilience analysis. It distinguishes between Risk of Failure—quantifying the likelihood of disruption—and Conditional Value-at-Risk (CVaR), which captures the severity of losses in extreme scenarios. By modelling these metrics as functions of the separation between stress and strength distributions, the framework reveals key trade-offs between reliability and economic impact. A risk-adjusted formulation is proposed to reflect stakeholder preferences, enabling planners to assess design robustness not only through failure probability but also through tail-sensitive loss estimates. While the methodology is illustrated through representative scenarios, no numerical results are presented. Future work will include quantitative validation and sensitivity analyses to demonstrate practical applicability for guiding investment decisions under uncertainty and for evaluating resilience strategies in the face of High-Impact, Low-Frequency events.

Heavy-duty long-haul trucks (>15 tons) represent less than 15% of the truck fleet but is responsible for about 65% of the CO2 emissions in the trucking sector in Germany. Battery electric trucks are one of the major options to decarbonise this sector.

The Lower Rhine region in Germany is part of the logistic heart of Europe. About 10% of all German trucks are registered here. Transport volumes are expected to further grow. The transition to e-mobility offers new opportunities for the logistic companies but also represents major challenges, in particular, what concerns implementation of an adequate charging infrastructure. Among others, these challenges are related to:

Availability of connection capacity in the distribution networks and coordinated planning of connection extensions over the transition period covering about a decade;

Availability of sites for depot charging;

Financing and mitigation of financial risks related to charging infrastructure investments;

Long periods for infrastructure planning and permitting;

Adequacy and stability of the regulative framework related to network connection and charging operations.

Motivated to support the industry, the ‘Logistikregion Rheinland’ contracted a study addressing these challenges.

In a scenario study we derived spatially resolved projections for the required charging capacity in the region up to 2045. The analysis showed that the transition still has to take off but the major change might happen in the relatively short period up to 2035. Charging demand in the logistics sector in the Lower Rhine region may grow to 5.6 TWh in 2035 and 8.8 TWh in 2045. Due to their long daily ranges and high specific energy consumption, tractor-trailer combinations account for about two third of this energy demand.

In parallel we set up an extensive stakeholder assessment. Together with experts from different involved industries and authorities, we analysed existing barriers companies are experiencing when attempting to implement the required charging infrastructure. The result of numerous explorative expert interviews highlighted uncertainties, lack of knowledge and the need for communication and coordination between different industries and authorities.

We concluded that, so far, charging connections in most cases can be supplied, based on higher utilisation of existing assets. In parallel networks are steadily reinforced and extended. However, looking at the steep growth of the required capacity in the coming years, charging infrastructure might become a bottleneck for the successful development of the logistics sector in the years between 2030 and 2035. The assessment identified pragmatic options for addressing these bottlenecks and allocated them to the stakeholders being in a position to tackle them.

The paper and presentation will summarise these findings and highlight key success factors for the coming decade. With the Lower Rhine region in mind we will translate the key insights and recommendations to an industry wide view.

Alongside society's development and electrification comes an increasing need for electrical energy. The transition towards renewable and sustainable energy production is therefore an essential topic in matching energy demand. For example, creative solutions like installing photovoltaics (PV) panels on unutilized areas such as parking lots can play a crucial role in meeting energy sustainability goals. However, these solutions should be economically feasible. This study aims to investigate whether implementing photovoltaic carports at the university building or an office parking lot is economically feasible and can help meet the facility's energy demand and the futuristic Electric vehicle (EV) charging demand. To determine this, real electricity prices, the facility's energy demand, and the ACN-Data dataset of EV charging sessions from a campus and office building are used. The economic metrics used are net present value (NPV), revenue, and payback period (PBP). For the energy matching with solar energy, metrics such as self-consumption (SC) and self-sufficiency (SS) are used. Sensitivity case including changing the EV charging pattern, as well as the EV charging fee, is considered.

The research project “Fuchstal-leuchtet” aims to investigate whether and how a stable grid operation can be achieved in practice within a network that lacks a centralized control structure and is powered and loaded exclusively by power converters. A key component of the research project is the investigation of the interaction between multiple power inverter systems and the identification and analysis of undesirable interactions between the control strategies of grid-following and grid-forming inverters under real-world conditions. Therefore, the first field test focused on studying the interaction of two grid-forming inverters with varying parameter configurations and control algorithms in an island grid. By selectively switching different loads, the dynamic and static f(P)- and V(Q)-behaviour of the grid-forming inverters was validated, and critical parameter configurations along with the resulting control interactions were identified.

Building on this, the second field test expands the existing islanded grid by integrating four wind turbines, each with a rated apparent power of 3 MVA. These turbines operate in accordance with the currently applicable technical connection guidelines for grid-following generation units in medium-voltage networks. The island mode operation conducted during the field test allows for the reconfiguration of the control parameters of the Farm Control Unit. This enables both the dynamic and static Q(V)- and P(f)-behaviour of the grid-following inverters to be defined and modified.

In preparation of this field test, parameter settings and test scenarios based on manufacturer specific RMS simulation models are developed to analyse the influence of outer-loop P(f)- and f(P)-control strategies of grid-forming (GFM) and grid-following (GFL) inverters on frequency behavior. Varying the control parameters enables the identification of undesired interactions between grid-forming and grid-following units, which can be triggered by disadvantageous parametrisations of both GFM and GFL inverters.

Within the scope of the paper, the following investigations are carried out in preparation for the second field trial, and the corresponding findings are presented:

• Influence of outer-loop control strategies of grid-forming and grid-following inverters on frequency behavior in the island grid

• Identification of critical parameter sets and their representation using RMS simulation models

• Evaluation of existing technical connection rules for grid-following generation units with respect to their applicability in island grid operation

Small-signal stability is becoming crucial for Renewable Energy-based (RE) power plants since converter-based systems are prone to interact with the grid subsystems and cause oscillations. Various methods have been introduced to evaluate the small-signal stability including frequency-domain and time-domain methods. The impedance-based stability analysis has become a trending method in the industry as it treats the power system components as black-boxed models and there is no need for exchanging of large amount of network data among different stakeholders. Hence, different TSOs are imposing new requirements for the stability compliance to be fulfilled by the RE power plant developers including impedance-based stability and additional time-domain studies. Despite the benefits of the stability compliance requirements, the execution of the studies and achieving a realistic outcome are very difficult and time-consuming due to the limitations in data sharing among stakeholders, validity of the models, unclear roadmap and workload. This paper proposes a framework to investigate the stability requirements involving all stakeholders and highlights the challenges over the stability compliance process. In addition, the stability study toolbox, which is developed internally within Vattenfall, is introduced and two case studies on an exemplary RE power plant are presented.

As part of the decarbonisation efforts in high-temperature industries, hydrogen is emerging as a key alternative fuel to reduce overall CO₂ emissions. In Europe, natural gas—composed of more than 90% methane—is currently the predominant fuel for glass industrial furnaces. Integrating hydrogen into this context requires the development of an industrial microgrid for on-site hydrogen production and storage. In this system, electricity is supplied by both the power grid and Renewable Energy Sources (RESs), serving the demands of a PEM electrolyser (ELY) and the electrical load of the furnace. The remaining thermal demand of the furnace is met by a combination of natural gas and hydrogen. The optimisation presented in this study foresees the Energy Management System (EMS) approach: for this industrial microgrid layout, the minimisation of operational costs of all the components is performed on an hourly time step, based on glass production, RES generation forecasts and gas and electricity price projections for the following 24 hours. The effectiveness of the system is proven by means of the microgrid simulation over a time period of 20 days, using real data from the industry. The optimisation model accounts for low-emission targets and furnace load constraints. The purpose of this paper is to investigate the flexibility and feasibility of hydrogen integration in a glass industrial setting.

Solar photovoltaic (PV) and wind energy are the most scalable and cost-effective renewable energy technologies available today. Their costs have declined significantly and are expected to continue falling, making them the cheapest sources of electricity across all technologies.

However, as variable renewable energy (VRE) sources driven by weather conditions, their ability to reliably power electric grids is often questioned. This is where the concept of firm power generation becomes critical. According to the IEA PVPS Task 16, firm power refers to the capability of a system of generation resources to meet electricity demand continuously—24 hours a day, 365 days a year.

A growing body of work shows that PV and wind can meet this firm power requirement cost-effectively when paired with:

• Battery energy storage systems (BESS)
• Dynamic curtailment (also known as implicit storage)

Cost-effectiveness improves further when:

• PV and wind are optimally blended based on local conditions
• A small share (e.g., 5%) of dispatchable thermal generation using GHG-free e-fuels is included to provide supply-side flexibility

Importantly, findings from IEA Task 16 suggest that cost-effective firm VRE solutions can be achieved locally, without the need for extensive long-distance transmission infrastructure. This challenges the common assumption that large-scale transmission is necessary to balance VRE variability and access high-resource regions.

This paper quantifies that assertion for the continental United States. Assuming a flat (baseload) demand and 5% e-fuel-based flexibility, we analyze how the cost of firm PV/wind generation changes with the geographic scale of the renewable generation footprint—from a single location to subcontinental regions.

Key Findings:

• Localized, self-contained firm power systems (within areas <50,000 km²) are economically viable across most of the U.S.
• Projected Levelized Cost of Electricity (LCOE) for firm power by 2050 in these self-contained systems ranges from 4.25 to 6.25 ¢/kWh

The paper also presents:

• Optimal PV/wind mixes for different regions
• Required levels of physical and implicit storage
• How these factors evolve with the size of the generation footprint to minimize firm power costs

The increasing integration of renewable energy sources into power grids requires adaptive strategies to maintain stability, especially

in island and distribution grids. This paper presents the development of a 200 kVA battery inverter with grid-forming control

for the integration of photovoltaics (PV) into island grids. The inverter uses a three-phase ANPC topology with two interleaved

legs and a DC-DC converter with flying capacitor topology. Usually, PV systems shut down as soon as they detect an island

grid. However, the integration of renewable energy is crucial for future grid reliability, especially in isolated or disaster-affected

regions. The energy management system aims to integrate PV systems into the grid during island grid operation, prevent battery

overcharging and ensure grid-serving functionalities. Using the VDE 4105 guidelines, the system controls PV active power by

adjusting the grid frequency and optimizes the battery’s state of charge (SoC) for reliability and durability. Laboratory tests with

Power-Hardware-in-the-Loop (P-HiL) demonstrate the effectiveness of the system in maintaining uninterrupted grid operation

and adapting PV power generation to the needs of the microgrid.

Reliable time series of wind power capacity are critical for analysing past production and for normalising historical data when training forecasting models. Databases of wind power installations can be used to create time series of installed capacity, but are often incomplete and temporally coarse. Any inaccuracies in magnitude or timing of installed capacity propagate into downstream analyses.

The Combined Power-curve and Quadratic optimization (CPQ) method iteratively fits a generic power‑curve model to derive a capacity factor time series, and solves a constrained quadratic program that identifies the capacity time series most consistent with observed production.

We validate the CPQ method on the high-quality data of the Danish wind power system, showing that it effectively reconstructs historical capacity time series with a MAPE around 1.9\% and a reduction in MAE of 22\% compared to the cumulative maximum reference method. Further, the CPQ-derived capacity time series can be used to normalise training data for a forecasting model to reduce forecast MAE by 1.2\% compared to using capacity time series based on database information. Requiring only aggregated production and publicly available wind data, the CPQ method can potentially fill information gaps in regions with poor data coverage.

Power Hardware-in-the-Loop (PHIL) testing enables the validation of grid-connected converters under realistic conditions by interfacing physical hardware with emulated grid scenarios. The accuracy of such tests depends critically on accurately representing the electrical grid at the point of connection. This work investigates the impact of physical versus emulated grid impedance in PHIL setups, with a focus on transient events such as voltage magnitude and phase jumps. Firstly, the effects of real-time simulation limitations - including sampling, digital filtering, and system latency - are analysed. Secondly, the influence of varying the physical-to-emulated impedance ratio is systematically evaluated using PHIL experiments with both grid-following (GFL) and grid-forming (GFM) converters. A novel current correction method is introduced to compensate for phase delays caused by digital filtering, ensuring that physical and emulated currents align while retaining noise suppression. Results show that purely emulated impedance can lead to oscillations or instability, particularly in GFM converters. Introducing even modest amounts of physical impedance (≈25%) substantially improves steady-state and transient behaviour, reduces overshoot, and stabilizes system response. These findings provide practical guidance for designing robust PHIL experiments where accurate transient performance and physical realism are critical.

The integration of Offshore Wind Power Plants (OWPPs) to power networks is considered as a major step towards the decarbonisation of energy production. These power plants are often connected to the onshore network via High-Voltage-Alternating-Current (HVAC) interconnections and are comprised of numerous devices, such as power converters, reactive power compensators and transmission lines. Each of these devices may introduce detrimental resonances and dynamic interactions between each other and with the onshore network, thus endangering its safe operation. To avoid these interactions and guarantee stability, detailed dynamic studies are necessary. Specifically, eigenvalue-based, small-signal stability analysis is considered a prominent method for identifying oscillatory modes under small disturbances. In this paper, a comprehensive stability analysis of a representative, HVAC-interconnected, OWPP is presented based on a small-signal, state-space representation approach. The dynamic models of all participating devices are presented and practical aspects of the analysis are addressed. Then, several parameter stability limits are investigated, with limitations resulting from both the steady state operation point conditions, as well as from the dynamic operation of the system. The linear model used for the study is validated in the time domain against a nonlinear electromagnetic transient model, developed in Matlab/Simulink.

Electric Vehicles (EVs) offer significant potential as Distributed Energy Resources (DERs) through balancing services or contingency reserves, yet practical implementations into ancillary service markets remain at an early stage and lack mature business use cases. Frequency Containment Reserve (FCR), the utility battery service for primary control reserve, presents an opportunity to harness aggregated EV symmetrical charging load for grid stabilization, in the form of a Vehicle-to-Grid (V2G) service. Such a service aligns with the well-established concept of Virtual Power Plants (VPPs), where distributed assets are aggregated to provide grid services. This paper investigates the functional model to provide FCR from public EV charging stations within the European energy market. Using the Smart Grid Architecture Model (SGAM), we develop a V2G‐FCR use case enabled by Electric Mobility Service Providers (EMSPs) orchestrating EV users' data interface, and Charging Station Operators (CSOs) acting as Balancing Service Providers. The resulting Computational Independent Model (CIM) defines roles and interactions across Business, Function, and Information layers, conforming to ENTSO‐E harmonized framework and IEC standards for pan-European adoption. The proposed model aims to enable EV owners and CSOs to gain financial rewards while contributing to grid resilience through FCR. The CIM design provides a conceptual blueprint for subsequent platform-independent and platform-specific development, establishing the theoretical foundation for scalable deployment of V2G-based FCR services.

Offshore wind power generation requires the deployment of complex transmission infrastructure, which significantly impacts the capital and operational expenditures of the overall project. The spatial separation between offshore substations—where wind turbine arrays are interconnected—and the onshore grid connection point can range from a few kilometers to well over 100 kilometers in some case studies. While high-voltage alternating current (HVAC) transmission systems are predominantly employed, high-voltage direct current (HVDC) systems are increasingly utilized for remote installations due to their superior efficiency over long distances. The breakeven distance at which HVDC becomes economically favourable over HVAC is a subject of ongoing research and is generally estimated to lie between 120 km and 160 km, contingent upon a multitude of technical and economic parameters.

In AC transmission configurations, reactive power management is a critical design consideration. Long submarine cables exhibit substantial capacitive behaviour, necessitating the integration of shunt reactors to supply inductive reactive power and maintain voltage stability. The inductance of these reactors must be dynamically adjusted in accordance with wind power output, as reactive power requirements are inherently linked to generation levels. Additionally, offshore transformers are typically equipped with on-load tap changers to facilitate voltage regulation within the offshore network.

This paper introduces an automated computational tool developed to address the aforementioned challenges and to optimize the design of offshore wind transmission systems. The tool supports hybrid configurations incorporating both overhead/underground lines (onshore) and submarine cables (offshore), and allows for the use of multiple voltage levels across different segments of the network. It also includes the strategic placement and sizing of reactive power compensation equipment. The tool evaluates a range of operational scenarios, characterized by varying wind power availability and grid voltage conditions at the point of interconnection, each associated with a defined probability. It ensures that the transmission system remains compliant with grid code requirements under all considered scenarios, avoiding violations of voltage, current, and power thresholds.

The optimization framework integrates deterministic mathematical techniques—specifically Optimal Power Flow (OPF) analyses—for fixed operating conditions, with heuristic algorithms to explore a diverse set of feasible technical solutions. The results are synthesized into a Pareto front that balances total project cost against the quantity of energy delivered to the grid.

A case study is presented to demonstrate the tool’s capabilities, highlighting the optimal technical configurations under varying prioritization criteria derived from the Pareto analysis. For each selected configuration, the corresponding OPF results across multiple operating conditions are detailed, illustrating the robustness and efficiency of the proposed design methodology.

The increasing affordability of electric vehicles (EVs) makes their widespread adoption inevitable. While extensive research exists on EV adoption and grid impacts, the influence of regulatory-based charging infrastructure development remains underexplored. This study investigates whether Germany's Building Electromobility Infrastructure Act (GEIG) can adequately support national EV adoption targets through a case study of Aachen's inner-city districts. Using scenario-based modelling, three deployment pathways (conservative, moderate, ambitious) are analysed, integrating building renovation projections with GEIG requirements to model charging point (CP) deployment across residential, commercial, and off-street parking facilities until 2045. Results reveal significant disparities across scenarios. The conservative rollout achieves an electric vehicle-to-charging point (EV:CP) ratio of 15.5:1, barely meeting Germany's 15:1 target. The moderate rollout reaches an 11:1 ratio, while only the ambitious rollout achieves an optimal 6.4:1 ratio staying close to the current ratio of 6.8:1. Power flow analysis of a chosen district (Steffensviertel) shows the ambitious scenario increases peak grid load by 22% and transformer loading by 13.5%, remaining within operational limits. The study concludes that current regulatory frameworks alone are barely sufficient to meet Germany's national targets. Achieving 100 % EV penetration by 2045 requires deployment strategies beyond regulatory compliance, providing critical insights for urban planners

The integration of renewable energy sources, especially offshore wind farms, poses a challenge to the stability of the electricity

grid. As the proportion of wind power grows, the variability and uncertainty of wind power generation leads to frequent grid

overloads, which require curtailment and result in significant energy losses. In addition, the increase in renewable generation

leads to higher intra-day and day-ahead market volatility. Both challenges can be addressed with storage, which allows for

economically optimized portfolio management and has the potential to alleviate congestion by acting as a buffer. However,

current control strategies often neglect the inherent uncertainties in both wind power forecasts and grid load dynamics.

This study tackles the critical issue of how to effectively manage co-located battery storage systems in wind park-grid setups

under uncertain conditions to reduce energy losses caused by frequent grid overloads. We explore the potential of incorporating

probabilistic forecasts into battery management strategies, which may improve the mitigation of overload-induced energy losses

compared to conventional deterministic methods. In addition, our studies analyze current market effectiveness, concerning energy

losses, and how regulations need to be adapted under changing revenue scenarios.

Tested on real world wind park data, we show that while even a simple rule-based strategy can significantly enhance the

effective energy generation due to buffering in the battery storage system, only an optimization strategy can truly trigger the

economic potential. Above that we demonstrate that an advanced stochastic optimization strategy, based on probabilistic day-

ahead wind energy forecasts, can significantly reduce price risks with respect to intraday marketing compared to a simpler

approach based on a deterministic day-ahead wind energy forecast alone. In a setup with a 1 EUR/MWh risk charge on intraday

prices relative to day-ahead prices, for instance, switching from deterministic to probabilistic forecasts improves overall market

gain by 0.1%. The advantage grows to up to 5% at a 100 EUR/MWh risk charge, assuming a battery sized at 33% of the wind

farm’s nominal power.

These findings indicate that accounting for forecast uncertainty not only enables more efficient use of wind energy, challenging

the prevailing reliance on deterministic models in battery dispatch, but also allows market participants to achieve greater financial

benefits through probabilistic forecasting in the future development of energy systems. This has important implications for the

design of future renewable energy systems and regulatory adaption, where flexible storage operation will be critical to manage

growing shares of variable generation. By providing a robust simulation model validated with real-world data, this work con-

tributes to the advancement of predictive control in energy systems, supporting the broader goal of increasing renewable energy

integration while maintaining grid reliability.

The increasing electrification of transport and heating sectors through electric vehicles and heat pumps presents significant

challenges for low-voltage distribution grids, leading to potential congestion situations. We present a decentralized agent-based

optimization approach for congestion management that leverages both legally mandated consumer flexibility and voluntary battery

flexibility. This multi-agent system enables individual households to participate in grid congestion management through

autonomous decision-making while aiming to preserve household data sovereignty and to achieve privacy-preserving coordination

via minimal information exchange. Our approach incorporates the German Energy Industry Act (§ 14a EnWG) framework

and utilises the Alternating Direction Method of Multipliers (ADMM) for decentralized optimization. Evaluation results using

the IEEE-33 test system demonstrate significant peak load reduction, complete elimination of thermal constraint violations, and

real-time feasibility. These findings demonstrate that decentralized coordination can effectively manage grid congestion while

maintaining privacy and regulatory compliance, offering a scalable alternative to traditional centralized approaches for future

smart grid implementations.

As power systems decarbonize and decentralize, the role of flexibility is becoming increasingly critical — not just for balancing supply and demand, but for ensuring the efficient and secure operation of the grid across all voltage levels. Local flexibility — provided by DERs such as batteries, electric vehicles, flexible loads, and distributed generation — can now play a vital role in addressing both local and system-wide challenges. Without coordination, the activation of distributed flexibility by a TSO or DSO in isolation can create conflicts, leading to inefficient outcomes or even operational risks. A coordinated approach to flexibility procurement — where TSOs and DSOs operate within a shared or interoperable market framework — can resolve these issues. This paper provides a comprehensive summary on NODES™ market and coordination approaches by highlighting real-world implementations and pilots of market-based flexibility procurement with TSO–DSO coordination in Norway, Sweden, Finland, Greece and Canada; and a forward-looking perspective on key enablers needed to scale coordinated flexibility markets across Europe, Canada. It demonstrates how well-designed flexibility markets can align local and system-level goals, reduce the need for costly grid reinforcements, and unlock new value streams for consumers and DERs. The real-world implementation of flexibility markets and projects from Norway, Sweden, Canada, Finland, and Greece show tangible pathways to integrate local and system-wide flexibility services, benefiting both the grid and market participants. By aligning procurement processes and creating transparent, interoperable market structures, system operators can ensure that flexibility is deployed where and when it delivers the greatest value.

The widespread adoption of electric vehicles (EVs) is creating new challenges for electrical distribution networks, particularly at public charging hubs. These sites vary in usage patterns, infrastructure types, and grid impact, making it critical to understand and model their electrical demand. This paper presents a data-driven framework to classify electrical demand profiles across multiple EV charging hubs, using real-world arrival and departure data. The approach is demonstrated using 2024 data from three ChargePlace Scotland (CPS) locations: a park-and-ride site, a stadium-based destination charger, and a town-centre multi-storey car park, each with varied charger types and utilisation characteristics.

The study uses probabilistic modelling and analytics to characterise key metrics, including occupancy factor, capacity factor, and half-hourly peak demand. Demand visualisations are developed using time-series heatmaps and density plots to capture temporal and spatial variations in hub usage. The analysis reveals significant variation in usage by site type and charger class. AC units show notably lower utilisation than DC chargers, with AC capacity factors ranging from 1.2% to 3.13%, while DC chargers peak at 11.9%. Overstay tariffs, user behaviour, and site context also strongly influence utilisation patterns.

Site A (park-and-ride) exhibits weekday morning peaks aligned with commuter behaviour; Site B (stadium) shows sharp weekend demand spikes linked to event schedules; and Site C (town centre) demonstrates long dwell times and consistently high occupancy but low energy throughput, suggesting inefficient use of charger capacity. These distinctions highlight the limitations of one-size-fits-all planning for EV infrastructure.

The classification framework developed supports stakeholders, including distribution network operators and site owners, in evaluating the effectiveness of existing infrastructure and planning for future demand. It also contributes to compliance with UK data transparency regulations for public charging networks. By providing the means to align infrastructure investment with actual usage patterns, the framework helps reduce the risk of stranded assets, manage peak loads, and support more flexible, resilient energy systems. This work provides a practical framework for designing smarter, scalable EV charging solutions grounded in real-world usage.

The grid conditions undergo continuous transformations due to increasing penetration of renewable distributed energy resources. In the future grid conditions will be significantly influenced by power generating converters. It is critical that these changes in the electrical grids do not negatively affect the stability. To mitigate that, the power generating converter control strategies must transition from grid following approaches to grid forming control. This general control change necessitated the development of new test methods. In addition to new test parameters (such as phase jumps, impedance scan or island operation capability), this also requires an appropriate testing facilities, and emulation of instantaneous changing of grid conditions in real time, in order to validate the correct operation and robustness of grid forming mode (GFM) converters and their control systems.

This work describes the concept of potential application of ACS6080-based grid simulator from ABB and its newly introduced current source mode, to support the testing of GFM converters with focus on their island conditions. The obtained simulation results demonstrate promising performance and provide a base for future investigations involving real equipment, towards approaching the viable alternative to conventional test setups, enabling a broader scope and greater diversity of GFM generation units conformity testing.

The Gaspésie network is a regional part of Hydro-Quebec’s grid that feeds a small amount of load over a vast region. The grid is radially connected to the main 735 kV backbone and is characterised by the presence of series compensated lines, back-to-back line commutated converters (LCC), small loads, weak grid and high IBR penetration. With more IBRs planned to be added to the region, Hydro-Quebec benchmarked transfer limits obtained through PDT simulations with EMT to ensure reliable operation of the grid. This article aims to share our experience doing transfer limits studies using EMT, both in terms of phenomena observed as well as issues encountered and solutions.

As solar-integrated residential electric vehicle (EV) chargers become increasingly common — driven by rising energy prices, grid constraints, and decarbonization efforts — evaluating their real-world performance is becoming essential. Laboratory testing, based on a guideline developed by the German research institutions Fraunhofer ISE and HTW Berlin (University of Applied Sciences Berlin), the German automobile association ADAC, and an industrial council, has shown a wide range of results for factors such as control behavior, standby power consumption, and control accuracy. While these measurements offer valuable insights for researchers and engineers, they are often too technical for end users. Therefore, a unified performance indicator is desirable.

This paper proposes a simulation-based performance indicator for residential solar-optimized EV chargers, inspired by established metrics used for PV battery systems. The methodology for evaluation includes: (1) measurement according to the guideline; (2) importing representative input data and parameterizing the simulation model; (3) simulating both an ideal and a real charger using laboratory measurement data; and (4) comparing grid consumption and feed-in values to express the charger’s performance as a percentage of the ideal benchmark.

By building on detailed laboratory results, the simulation model combines accuracy regarding key features with the scalability of analyzing longer time series. The proposed indicator enables more transparent product comparison and informed decision-making for stakeholders. Initial findings show that some chargers achieve only 75% and 92% of the performance of an ideal system under identical conditions, revealing considerable potential for optimization. This contribution presents the methodology and introduces a novel metric that highlights, for the first time, significant efficiency differences among commercially available residential EV chargers.

Denmark’s goal of carbon neutrality by 2050 requires a power system largely based on renewable energy, leading to the gradual replacement of synchronous machines with grid-following inverter-based resources. This transition reduces system strength, creating challenges for maintaining voltage and frequency stability. Grid-forming (GFM) control has emerged as one of the promising solutions to address the challenges. In 2023, the Danish TSO Energinet launched the “Deployment of Grid Forming Technology in the Danish Power System” project to evaluate commercial GFM products. Within this project, the GFM capabilities of different technologies were assessed through system-level EMT studies of the Danish grid.

This paper presents a detailed study of an incident that happened in eastern Danish power grid (DK2) in 2020, where sequential faults caused a network split at 400 kV backbone, synchronous condenser (SynCon) tripping, and HVDC blocking. The incident is revisited by replacing the SynCon with either a GFM STATCOM or an E-STATCOM, evaluating their effectiveness in mitigating the instability. Comparative results indicate that both devices provide better voltage control compared with the SynCon, with the E-STATCOM demonstrating further improvements in damping capability. These findings underline the potential of GFM (E-)STATCOMs to ensure security and resilience in future renewable-dominated power systems.

This publication presents the design of the Integrated Local Flexibility Market (LFM) developed within the Greek pilot of the EU-funded OPENTUNITY project. The pilot involves Hellenic Electricity Distribution Network Operator (HEDNO) as the Distribution System Operator (DSO), Independent Power Transmission Operator (IPTO) as the Transmission System Operator (TSO), and NODESTM as the Flexibility Market and Platform Operator. Flexibility Service Providers, despite actively participating in the LFM, are excluded from the study as the main concept surrounds TSO-DSO coordination. Within the Greek pilot, HEDNO will participate in the Integrated LFM to address local congestion, while IPTO will evaluate the procurement of flexibility for frequency control, and specifically for manual Frequency Restoration Reserve (mFRR). Resources will be connected to the distribution grid, employing NODESTM’ ShortFlexTM product. The market framework includes a dedicated rulebook, asset registration, and grid replication, facilitating efficient flexibility procurement. A key innovation is the coordination mechanism between TSO and DSO to avoid conflicting activations, tested through three distinct operational scenarios. These scenarios are evaluated based on resolution time and the proportion of successfully traded flexibility. The pilot demonstrates how integrated flexibility markets can enhance grid reliability and support scalable TSO–DSO cooperation.

In back-to-back converter systems used with doubly-fed induction generators (DFIG), rotor-side converter (RSC) and grid-side converter (GSC) generate fundamentally different harmonic spectra due to the distinct impedances they operate against. The machine’s inherent inductance naturally attenuates the RSC spectrum, whereas the GSC relies on an LCL filter designed around a fixed switching frequency to meet grid-code requirements. This asymmetry motivates using different switching strategies for the two converters: the GSC maintains a fixed frequency based on filter design, while the RSC can be tuned for improved efficiency.

In this study, the switching frequency of the generator-side converter is reduced from 3000 Hz to 2000 Hz to lower switching losses. However, this reduction increases harmonic distortion, particularly in frequency regions where filtering is less effective.

To mitigate the resulting harmonic content, a sinusoidal periodic carrier frequency (PCF) modulation technique is introduced. This method imposes a controlled wobble on the carrier frequency over time. While PCF modulation helps distribute harmonics across the spectrum, it may inadvertently increase low-frequency harmonic energy, where filtering is inherently weaker.

To overcome this limitation, the proposed method leverages resonant interactions between sideband harmonics generated by the PCF effect and those intrinsic to space vector modulation (SVM). By selecting PCF frequencies that are integer multiples of the fundamental frequency, the harmonic spectrum can be shaped more advantageously. The key innovation lies in the resonant synchronization of the PCF frequency at six times the fundamental frequency, with precise phase alignment to the base waveform. This configuration effectively redirects harmonic energy away from the critical low-frequency region and into higher-frequency bands, which are more amenable to attenuation by the generator’s natural inductance.

The study is based on original simulation models and spectral analysis of a 6 MW DFIG system. Multiple PCF parameters, including peak carrier-frequency deviation and phase angle, were tested to identify optimal conditions for harmonic redistribution. Initial simulations at a 2000 Hz switching frequency without PCF revealed severe harmonic violations, with grid-side transformer current magnitudes reaching 240 percent of grid-code limits. Conventional PCF modulation proved insufficient, as harmonic energy remained concentrated in low-frequency bands with inadequate filtering.

In contrast, the proposed resonant PCF–SVM approach successfully redistributed harmonic energy into higher-frequency regions, resulting in full compliance with grid standards at 93 percent of the allowable limit. The results demonstrate that this technique maintains current waveforms within harmonic limits even at reduced switching frequencies. Its straightforward implementation makes it highly practical for enhancing converter performance in large-scale wind energy applications.

Grid-forming converters play a key role in grids with a high share of renewable energies. Clear definitions and verification procedures for grid-forming Electricity grids with a high proportion of renewable generation require grid-forming converters to ensure system stability. In

order to accelerate the deployment of this new technology, technical requirements for grid-forming converters are needed to form

the basis for new grid codes.

This work makes a new proposal to make the voltage source behaviour, the core property of grid-forming converters, verifiable.

For the first time, this proposal avoids analysing the response of the converter in terms of current or power or requiring islanding

capability. Instead, the voltage source characteristics are verified directly via the behaviour of the voltage space vector of the

converter. This makes the process simple, comprehensible and also applicable when the converter system has hardly any energy

reserves to feed out additional active power.

In an exemplary verification procedure, several converters are measured and analysed on a test bench. The procedure proves that

the novel approach can be accurately executed with real measurements.

Hybrid power- and voltage-based synchronization control (HSC) has been demonstrated to effectively enhance the transient stability of grid-forming converters. However, when combined with virtual admittance control, the voltage-based synchronization component introduces an equivalent reduction in the power reference, which results in inaccurate steady-state power tracking. To address this issue, this paper proposes a current-feedforward (CFF)-based HSC scheme. The added CFF eliminates the steady-state power tracking error while preserving the damping effect provided by HSC and equivalently increasing the internal voltage magnitude, thereby improving transient stability. The effectiveness of the approach is confirmed by simulation results.

Renewable generation in the NEM (and WEM) in Australia have been facing increasing curtailment in recent years, with multiple utility-scale solar farms now seeing annual curtailed generation of over 50%, resulting in sub-economic commercial outcomes and significant operational challenges. This scenario is also impacting wind generation with drops of 5-10% in capacity factors already occurring across all NEM and WEM regions.

Among the utility-scale curtailment, unresponsive rooftop PV continues to grow at ~3.5TWh per year, resulting in 20-25% of spot market outcomes being negative in some regions, mostly between 10am-3pm and especially on weekends. And whilst utility-scale BESS continues at a 1GW/yr, it is not enough to prevent the curtailment or low prices.

Therefore, utility-scale hybrid generation is now far more attractive, with a 100MW Hybrid Solar farm entering full commercial operation in 2025. Cunderdin Hybrid Solar, a 100MW Solar, 55MW/220MWh DC-coupled BESS in the WEM, provides a useful real-world use case of the difference between dispatch outcomes when compared to the 100MW Merridan Solar farm, located 100km away. This presentation will provide some of the learnings and observations from the front line of that project in assisting Australian participants with commercial, technical and operational challenges of increasing renewable penetration.

Renewable energy sources and electric vehicles (EVs) that do not emit CO₂ are expected to become more widespread to achieve carbon neutrality. A balance between energy production and consumption in a local area is essential to ensure energy security.

This paper focuses on the power supply-demand balance of a regional microgrid model using renewable energy sources and V2X-controlled EVs. The microgrid is assumed to be located in the northern part of Hokkaido, a cold and snowy region where using EVs is relatively challenging.

The modelled microgrid includes the power demand from a town hall, a hospital, and a welfare center, the power supply from a biogas power plant and a photovoltaic power plant, and six official-use EVs as batteries. The author's previous study did not consider practical vehicle behavior data, such as how EVs drive and park. Thus, the impact of V2X-controlled EVs on the power supply-demand balance was not analyzed precisely.

The behavior of official-use vehicles in the town of Hokkaido was measured to improve the accuracy of the microgrid's power demand-supply analysis. The measured data were used to analyze the changes in EV batteries' state of charge (SOC) and the daily parking time ratio.

Six actual official vehicles were selected to collect behavior data, considering vehicle types, usage purposes, and the total mileage necessary in the modelled microgrid. GEOTAB, a telematics device equipped with GPS, was installed in the six practical vehicles to measure data such as mileage, travel time, and battery state of charge. The measurement period started in August 2024.

The daily initial SOC of EVs is an essential parameter in maintaining the power demand-supply balance in the microgrid using V2X-controlled EVs. The measurement results show that the daily initial SOC of official-use vehicles in the modelled microgrid can be set at 89 %.

The ratio of time that official vehicles were parked at the town hall per day was analyzed using the measurement data. The correlation between the average temperature on each day and the parking time ratio of EVs and hybrid vehicles(HEVs) was investigated. The monthly-average correlation coefficient was calculated. The results showed that drivers' intention to use EVs decreases as the temperature decreases, and the parking time ratio tends to increase. In months with an average temperature of 5 deg Celsius or lower, a negative correlation was observed between EVs and HEVs' average parking time ratio and the average temperature.

The authors will conduct simulations of the power demand-supply balance in a microgrid composed of a photovoltaic power plant, a biogas power plant, and V2X-controlled EVs. The measured vehicle behavior data shows that vehicle behavior can be classified based on temperature conditions and used to build EV simulation models. Since the official vehicle behavior data will soon be accumulated for one year, the full paper will report the detailed analysis of the vehicle behavior data and the microgrid simulation results.

Renewable energy sources (REs) and electric vehicles (EVs) are expected to become more widespread to achieve decarbonisation. Microgrids, the energy systems that best utilise REs, are also expected to be widely installed. Since REs have fluctuating output power, batteries should be installed with REs in the microgrid. However, the installation of batteries in a microgrid requires high costs.

The authors have researched the reuse of used batteries exhausted from electric vehicles (EVs) as on-ground batteries to substitute for new batteries and maintain the power demand-supply balance in the microgrid. The authors proposed a battery charge/discharge control method for coordinating REs, batteries and loads in a regional microgrid in a rural area. They also confirmed the proposed method through Model-IN-the-Loop (MIL) simulations.

This paper proposes a method for designing the required REs' power output, the required capacity of used batteries, and a battery charge/discharge control method to keep the power demand-supply balance in a rural microgrid. The paper also shows the results of one-year-long MIL simulations to confirm the proposed control method through MIL simulations.

The power consumption of dairy farms, such as milking machines, ventilation fans, and air conditioning units, was assumed to be loads in a rural area. The rural area's power demand was classified into the middle and summer terms. As a renewable energy source, a biogas power plant using livestock manure was assumed, and the biogas power plant's power output was supposed to be almost constant. A used lithium-ion battery (LIB) with a relatively large capacity was presumed to be installed.

The basic principle of the LIB charge/discharge control method is that if the load-consuming power is greater than the biogas plant's output power, LIB is discharged. On the other hand, if the biogas plant's output power is greater than the load-consuming power, LIB is charged.

The required output power of the biogas power plant was calculated assuming that the energy load-consuming power plant and the energy generated by the biogas power plant in a day coincide. The required capacity of the battery was calculated assuming that the charged energy and the discharged energy in a day coincide.

Since the battery state of charge (SOC) may reach its upper or lower limit in the summer term, the authors proposed another control method to slightly vary the biogas plant output power according to the LIB's SOC.

To confirm the proposed method, MIL simulations were conducted using OPAL-RT, a real-time simulator running on the CAD base of MATLAB/Simulink. The real-time simulator was set to a calculation mode that allows simulations to run faster than real time, and simulations were conducted using one-year-long data at 100 microsecond increments.

The simulation results showed that the ratio of energy purchased monthly from a power company grid outside the microgrid to the annual load consuming energy was about 2.4 % at maximum.

These results confirm that the rural microgrid with a load, a biogas power plant, and a battery can maintain a good　power demand-supply balance.

Renewable energy (RE), hybrid electric vehicles (HEVs), and electric vehicles (EVs) are expected to become increasingly widespread alongside efforts toward carbon neutrality. In Japan, photovoltaic (PV) power is the most widely deployed RE source, but its output is highly dependent on weather and exhibits significant short-term fluctuations. The target region of this study, Hokkaido, is Japan’s northernmost prefecture, characterized by vast land, cold climate, and extensive dairy farming. As a result, biogas (BG) generation using fermented cattle manure is widely adopted; however, BG output cannot be flexibly adjusted in the short term and is generally used as a baseload power source. Combining highly variable RE with power sources that have limited adjustability makes it difficult to maintain a supply-demand balance. Introducing microgrids in small regions and integrating RE with batteries is an effective solution to stabilize supply and demand. However, in kW-scale systems, deploying new batteries remains economically challenging.

The authors have previously proposed an emergency-oriented microgrid model that utilizes EVs as virtual power lines and combines reused EV batteries with RE to stabilize power supply. However, the application of such systems for normal daily operation has not been sufficiently investigated.

In this study, an extended microgrid model for daily operation was developed based on the previous emergency-oriented model, targeting a small municipality in Hokkaido. The microgrid integrates PV and BG generation and includes a V2X system to provide supply-demand regulation.

To construct EV operation patterns, municipal gasoline vehicles and EVs were equipped with GPS loggers to collect multi-day driving and parking data. Two consecutive EV operation patterns with different driving and parking behaviors were employed to design the V2X control strategy.

The microgrid load consists of three public facilities—a hospital, a welfare center, and a town hall—assumed to be connected via the municipality’s distribution network. The V2X system comprises five EVs and stationary batteries utilizing reused lithium-ion batteries (LIBs) from EVs, with capacities of 62 kWh and 59 kWh, respectively. Under V2X control, the EVs and LIBs perform charge-discharge operations to maintain supply-demand balance, with power exchange with the commercial grid if additional regulation is needed. In addition, high-output reused nickel–metal hydride batteries (Ni-MH) from HEVs, with a capacity of 8.7 kWh, are installed on the PV side to smooth short-term PV output fluctuations and supply a combined output to the microgrid.

Simulations using MATLAB/Simulink over five weekdays were conducted to evaluate the RE utilization ratio. The results confirmed that the RE utilization ratio exceeded 99.9% for both EV operation patterns. These findings demonstrate that the V2X system can effectively coordinate EV and LIB operation to stabilize the microgrid’s supply-demand balance under normal daily conditions.

Disturbances such as power imbalances or faults propagate in the form of power-frequency waves, traditionally shaped by network characteristics and synchronous machine dynamics. With increasing penetration of inverter-based resources, the dynamics of wave propagation is fundamentally altered. The work examines how grid-forming converters can affect the synchronization process by creating discontinuities that affect wave reflection, attenuation, and oscillatory behaviour. Building on this framework, the role of wide-area damping control as a complementary communication-based synchronization mechanism is explored and discussed. Numerical experiments illustrate the impact of grid-forming placement and coordination on disturbance dynamics, highlighting differences between different possible cases. The results confirm that, while grid-forming converters reshape propagation mechanisms, coordinated wide-area control can significantly support the synchronization between the oscillating elements of the system.

The enormous installation of renewable energies and flexible devices (like wallboxes, storages or heatpumps) and the resulting increase in grid usage is leading to ever greater challenges but also opportunities for the market, grid and system. The expansion of the electricity grids to cope with short-term power peaks runs contrary to the goal of an affordable energy transition. However, in order to improve the integration of renewable energies as well as market, grid and system services, it is essential to enable and utilize market integration for micro-flexibility and flexible households as a whole.

Market players currently act independently and pass on market-oriented control actions directly to micro-flexibilities in the low-voltage grid. High simultaneities due to uniform market-based price incentives can lead to congestion situations and overloads in the low-voltage grid. Although grid operators have reactive measures to resolve congestion (§ 14a EnWG). These unplanned interventions are counterproductive for market optimization and usually have to function in a targeted manner in a short-term, targeted manner in order to eliminate the congestion.

For more planning security for the grid and market, proactive harmonization with an envelope curve is to be used for the early communication of free grid capacities, which can be used for market optimizations. The aim of the envelope curve concept is to strategically integrate flexibility in the low voltage, avoid load peaks, strengthen system stability and usefully supplement curative control elements. Regulatory anchoring is required in order to fully exploit the potential of this solution.

This paper presents a system-wide approach for contingency severity screening intended as a practical and scalable precursor to full dynamic security assessment (DSA). DSA is the standard practice used by Transmission System Operators (TSOs) to ensure that power systems remain stable following disturbances, with key variables—such as voltage, frequency, and thermal loading—kept whithin defined dynamic performance limits. However, applying DSA comprehensively across all credible contingencies and operating points is prohibitive, making a pre-screening stage indispensable. Commonly used static-security filters offer limited insight to transient dynamics, motivating the development of alternative screening strategies. To support early-stage analysis and prioritization, three static indicators are devised as proxies for dynamic behaviour, grounded in the power-angle characteristics determining transient stability. For each n-1 contingency, these indicators provide a severity estimate and serve as inputs to a supervised learning model trained on labels derived from time-domain simulation. This approach aims to reflect how each disturbance migth impact system stability, consistent with the objectives of DSA. Contingency rankings derived from these estimates serve to guide further analysis, enabling TSOs to focus dynamic simulations on the most critical scenarios.

This work presents a Voltage Source Converter (VSC) controller that operates simultaneously as GFL and GFM. The GFL part functions as a GFL in a conventional wind generator (WG), and the GFM part can ensure grid support. This solution does not require additional hardware and is named the Hybrid Control Converter (HCC). The HCC was applied to the grid-side converter of a Type IV WTG, which was modelled in PSCAD. This approach aims to have a WTG that, in steady-state conditions, operates as a GFL converter guaranteeing MPPT, if its active power reference is the MPPT power, and during a disturbance in the grid, operates seamlessly as GFM, providing frequency and voltage support, like a synchronous generator. Simulation results are presented to show the latest advances of using HCC, such as: (i) black start capability, supplying power to a load or not; (ii) operation continuously isolated from the grid, allowing 100% wind generation, provided there is enough wind; (iii) ability to operate with or without a PLL algorithm, which could be an advantage for the cases highlighted in the literature in which instability problems in the converter control system are attributed to the PLL.

Hydrogen production via water electrolysis is a promising pathway for decarbonizing renewable based energy systems by enabling large-scale energy storage and a flexible power supply through fuel cells. Among the available electrolysis technologies, solid oxide electrolysis stands out due to its higher efficiency potential compared to conventional alkaline and proton exchange membrane (PEM) methods. A critical component of such systems is the AC/DC power converter which significantly affects the overall performance of the electrolysis process. This paper presents a detailed modeling and experimental analysis of the power conversion system used in a solid oxide electrolysis-based Power-to-Hydrogen (PtH) platform. The study is conducted on a full-scale experimental setup at Aarhus University's research laboratory in Foulum and was carried out as part of the REACT-EU project in collaboration with Topsoe as the industrial partner. The modeling approach is grounded in real-time measurements, incorporating harmonic analysis of interfacing components that may influence the PtH system. A key contribution of this work is the development of a high-fidelity digital model or digital shadow of the power conversion system which is validated through experimental data. The model's accuracy is confirmed by direct comparison with dynamic and steady-state performance measurements from the operational platform. Moreover, through comprehensive power quality analysis the strengths and limitations of the system under real operating conditions are investigated. The experimental findings not only validate the proposed model but also present valuable insights to improve the efficiency and grid integration of PtH applications.

At the core of Power-to-X (PtX)systems Power-to-Hydrogen (PtH) technology which produces hydrogen through electrochemical electrolysis plays a crucial role. Due to the rising global demand for hydrogen and the growing need to store variable renewable energy sources, the development of technologies to convert renewable energy into hydrogen is increasingly essential. Electrolysis as a clean and efficient process that uses DC current which is converted from the AC output of renewable energy resources to split water into hydrogen and oxygen is vital for producing green hydrogen and enabling long-term energy storage. However, integrating large-scale PtX systems into existing energy grids introduces significant power quality challenges that must be addressed to ensure reliable and stable grid operations. These challenges will become more critical as investigations show that PtX will account for 50% of future electrical consumption. Therefore, harmonic analysis will need to be strengthened in relation to summation rules, harmonic modeling and future power system design. This study proposes a comparative analysis of control frameworks for harmonic filtering in a PtH energy conversion system using the AC/DC universal diode bridge-based topology. This topology is widely used in industrial applications due to its low cost, simplicity and robustness. In order to enhance the power quality of the simulated PtH energy conversion system, two different types of control frameworks for harmonic filtering are designed in this paper. Simulation results demonstrate the effectiveness of the proposed harmonic filtering schemes, utilizing the presented control frameworks to improve the power quality of the power conversion system. Furthermore, a comparative investigation and discussion of the designed harmonic filtering schemes shows the impact of the control frameworks on power quality improvement and the resulting AC side signal after modifications. Based on the results of this paper, the most efficient control framework is selected and an extended version of the active filter equipped with this control scheme will be utilized in the full-scale experimental setup at Aarhus University's research laboratory in Foulum. These findings demonstrate the importance of the power conversion system in PtH plants and the potential for enhancing power quality through the implementation of advanced power compensation devices.

Background and objective

Japan government published the 7th Strategic Energy Plan (the Strategic Plan) in February, 2025.In the plan, the demand and supply balance of energy and electric power in 2040 was indicated, emphasizing that there are many uncertainties including demand and supply of electric power and energy, energy network, fossil fuel supply and price, carbon emission cost. In the planning process, the authors participate in the integration cost estimation (LCOE*) of generation technologies.

The penetration of variable renewables has been impacting an operation of a power system all over the world. In order to make the best use of zero emission generation such as variable photovoltaic and wind generation (vRES) and nuclear, and to keep the economy and security of electric power, it is critically important to secure flexibility in a power system.

In this study, we analyze the impact on operational cost under different scenarios of generation, flexibility supply from traditional generators, distributed generators, demand responses and energy storages in Japan in 2040.

Methods used

The method used is a production cost analysis tool “MR” with network constraints using real demand and supply condition of the future power system of Japan.

MR has a capability to set the requirement for different flexibilities and to define supply capability of various sources including traditional generation and distributed resources to optimize the generation dispatch, flexibility dispatch and demand shift to minimize the operational cost. MR also has a capability to analyze transmission system congestion and short circuit capacity of the nodes in the transmission system.

Main results obtained

We estimate the several demand and supply scenarios of Japan in 2040 based on the Strategic Plan and publicly available data. We also estimate the future requirements for flexibilities (FCR, S-FRR, FRR, RR, and RR-FIT) dependent on the capacity of vRES and demand level in the future from the current requirements in the flexibility market. Flexibility supply from traditional generators and DERs are estimated current and future technology establishment.

The results of the production cost analysis will show the followings:

Distributed resources such as vRES, demand technologies and batteries are heavily expected to supply flexibilities in cooperation with traditional generators, and

The requirement for flexibilities has a critical impact on the cost of system operation to affect the selection of the desirable transition pathways of a power system.

The implications from the analysis results are:

It is essential to diversify the supply of flexibilities and improve the flexibility needs,

To show the future requirement of flexibilities is important as a market information.

It is critical to establish rules including a grid code in order to enable DER involvement.

With the widespread adoption of inverter-based resources, the large-signal transient behavior of internal control loops has become a critical factor for protective relaying. This paper develops detailed large-signal transient models for the inverter’s PLL and DC-link control loops and employs time-domain simulations to perform parameter sensitivity analysis. Key parameters—including PLL bandwidth, filter time constants, DC-loop PI gains, and DC-link energy storage components—are varied to assess their impact on relay operation. Simulation outcomes indicate that protective relay response times and selectivity can vary noticeably across parameter settings, though the exact effects depend on specific disturbance scenarios. The study offers a conceptual framework for protection setting in inverter-dominated grids to ensure reliable protection performance.

As power systems decarbonise, offshore wind power plants (OWPP)s have been proposed as replacements for conventional blackstart units. This work reviews state-of-the-art OWPP blackstart capabilities, focusing on HVDC-connected OWPPs, whose wind turbine generators (WTG)s—upgraded with grid-forming (GFM) controls in their voltage source converters (VSC)s—will lead the restoration operation.

Traditional restoration guidelines rely on synchronous generators, but modern standards emphasise converter-based resources for resilience. OWPPs can theoretically provide fast blackstart service, but practical realisation remains challenging. Electromagnetic Transient (EMT) simulations suggest that a few GFM WTGs can energise AC networks and HVDC links. Studies show both hard and soft energisation methods—a hard start applies full voltage in one step, whereas a soft start ramps up to limit surges. This review synthesises research breakthroughs, knowledge gaps, and standards, distilling them into five main challenges:

1. GFM/Grid-Following (GFL) WTG mix: Not all WTGs in a large OWPP will be GFM, and the minimum GFM share needed to stabilise a dead network is unclear; studies often assume 100% GFM or add a battery energy storage system (BESS), leaving mixed GFM/GFL dynamics poorly understood.
2. Energisation sequencing: The optimal sequence of a system restoration—from self-start at the WTG-level to blackstart an HVDC-connected OWPP and beyond—is not established. Few studies detail the full procedure, and uncertainties remain in controlling inrush currents and overvoltages at each stage, especially with large HVDC DC-link capacitors.
3. Control interactions: Interactions between multiple GFM VSCs and remaining GFL units—WTGs, HVDC transmission, BESS, reactive compensation, etc.—remain under investigation. Unintended coupling can occur when GFM inverters run without coordinated control. Most studies focus on a single GFM, and system-wide stability analyses are lacking.
4. WTG sub-model limitations: Many simulation studies oversimplify WTG models by neglecting detailed models of the machine-side converter (MSC) of the GFM WTGs, turbine shaft dynamics, or assuming an ideal DC-link. Such simplified modelling can misrepresent phenomena like DC-link capacitor inrush. More detailed WTG models are needed.
5. Validation, standards and protection: No full-scale OWPP has performed an autonomous blackstart. Testing and certification standards remain nascent; design verification, protection coordination (e.g. FRT/UVRT thresholds, current-limit settings, relaxed relay logic during soft-ramp), and on-site testing for OWPP-led blackstart are still insufficient.

The recent April 2025 peninsula-wide blackout in Spain—triggered by two rapid generation trips during a period of unusually high penetration of converter-based resources—has reignited debate on inertia-less systems and highlighted the urgency of developing GFM, blackstart-capable converter technology to ensure stability and restartability in renewable-dominated grids.

This literature-based analysis finds GFM-controlled OWPPs promising but underutilised for blackstart; prior studies demonstrate feasibility in simulations and small tests yet highlight unresolved stability, control coordination, and component stress issues. Key knowledge gaps include mixed GFM/GFL behaviour, HVDC energisation from wind, and need for high-fidelity WTG models. By bringing together findings from diverse sources into a single narrative, this work provides a comprehensive overview of the state-of-the-art and identifies critical research gaps. These insights set the stage for developing robust blackstart-capable OWPPs and inform stakeholders of the technical challenges that must be overcome to certify OWPPs as blackstart units.

Iceland is a quite large country (100,000 km²) rich of energy resources but with a small population (400,000). The electricity production is 20 TWh (14 hydro, 6 geothermal). Wind energy has not been utilized so far, but conditions in Iceland for wind energy are good (capacity factor 0.4). It is possible to produce lot of electricity in Iceland by wind. If we assume it is possible to produce 2MW per km² of land area, 20 TWh can be produced by utilizing only 1% of Iceland. By utilizing 5% of Iceland, 100 TWh can be produced (average power 11,400 MW).

Wind energy is unreliable, varies from time to time, therefore mainly two options for utilizing wind produced electricity in Iceland have been mentioned :

Sell ​​it abroad by HVDC submarine cable

Use it to produce electrofuels

Many HVDC submarine cables have been installed in Europe in recent years, the longest being the Viking Link, 765 km. But still no HVDC submarine cables have been laid between Iceland and Europe. One reason is probably the distance, but cable between Iceland and Scotland would be more than 1,000 km. But to carry 100 TWh to Europe, one cable is not enough. For that more than 15 cables are needed (each 700 MW).

But will 100 TWh of electricity to Europe change anything? Electricity consumption in Great Britain is ca. 4.2 MWh per capita per year and 5.5 MWh in Germany. 100 TWh is electricity consumption of 20 million people society (if 5MWh per capita). So wind energy utilization in Iceland does matter for Europe.

The North Atlantic is different weather area than Europe. Often completely different wind in Iceland than in Europe. More variability in wind between areas improves the whole system.

Connection from Iceland to Europe also opens possibilities to use the wind energy on east cost of Greenland.

Carrying electricity from Iceland to Europe is costly. Too costly? The electricity will always be cheaper at the Icelandic end than the Europe end of the cables. Utilization of the wind in Iceland and cables to Europe - which give more reliability - could lead to more energy intensive industry in Iceland.

If the wind would be utilized in Iceland, where should the windmills be located? In agricultural areas? Or in the uninhabited mid-highland? Or in uninhabited lowland regions? Large scale use of wind energy in Iceland gives opportunity for huge positive economical effects on Iceland’s rural areas. Depends on political will.

The rapid growth of photovoltaic (PV) systems in distribution networks has increased the need for advanced voltage regulation strategies. Smart inverters (SIs), equipped with voltage control functions such as fixed power factor, Volt-Var, and Volt-Watt control, as well as communication capabilities with external systems, are expected to manage local voltage profiles by adjusting active and reactive power. However, a major challenge remains in determining, at each prosumer endpoint, which control logic—such as power factor or Volt-Var control—should be applied and how its parameters should be set according to the local grid conditions.

To tackle this issue, this study proposes a data-driven optimization framework for individually customized inverter control settings. Specifically, we focus on a personalized federated learning scheme that leverages locally measured voltage and PV generation time-series data, summarized into compact statistical descriptors (i.e., approximate representations of the joint distribution of voltage and PV output, modeled as a mixture of basis distributions capturing their cooccurrence patterns). This enables evaluation of various control settings without relying on detailed distribution system models. The objective function considers both the total curtailment and fairness in PV output reduction, using a generalized squared Hellinger distance to quantify imbalance. By coordinating parameter updates among prosumers with similar operational contexts, the proposed method achieves scalable, model-free optimization. Simulation results on a high-PV penetration distribution system confirm that our approach enables more effective voltage regulation and fairer utilization of renewable generation capacity across the network.

The transportation sector remains a major contributor to global carbon emissions. While private electric vehicles (EVs) are increasingly widespread, the electrification of heavy-duty vehicles (HDVs) that constitute fleets, including buses and long-haul trucks, is critical for achieving deep decarbonisation. However, the clustered and high-power charging demand of HDVs, particularly at depots, poses significant challenges for electricity distribution networks and charging station operators. Prior research has relied primarily on stochastic simulation models that, although valuable, often fail to capture localised variability, seasonal fluctuations, and operational factors for accurate grid infrastructure and charging schedule planning. This paper presents an empirical analysis of real-world anonymised charging data collected across diverse charging sites, including fleets of Rideshare vehicles, Shuttle buses, and Trucks operating in urban and semi-urban settings. By examining charge session characteristics and site-specific load profiles for various fleet types, we offer insights into their operational nuances, spatio-temporal variations and the predictability of load profile. This study shows that accounting for site type and usage, together with seasonal effects and charging behaviour, informs data-driven planning of resilient, cost-effective EV charging infrastructure.

The Japanese government has announced policies to achieve carbon neutrality by 2050 as a countermeasure to recent abnormal weather and global warming. To realize carbon neutrality, the power sector must maximize the installation of renewable energy sources.

Offshore wind farms are expected to be widely implemented since offshore locations offer better wind conditions than onshore sites. However, it is a significant challenge that regions with high potential for offshore wind farms are often far from power demand centers. A high-voltage DC transmission (HVDC) system is a promising transmission method for long-distance transmission.

To utilize the HVDC system to improve power system stability, this paper proposes providing a two-terminal HVDC system between an offshore wind farm and an onshore power grid, with a damping control function to mitigate power oscillation caused by onshore grid disturbances. Simulation results to confirm the proposed method are also reported.

The simulation model consists of an offshore wind farm, a two-terminal DC transmission system, a synchronous generator adjacent to the HVDC system, double-circuit AC transmission lines, and an infinite bus power source.

A power oscillation damping (POD) controller was added to the onshore terminal of the HVDC system to suppress a power swing caused by AC grid disturbances, such as a ground fault. In the POD controller, frequency fluctuations in the onshore grid are detected, and the detected fluctuations are modified by a phase compensator and added to the d-axis current command value for the AC current controller. The proposed control method supplies additional power from a DC capacitor of the onshore terminal to the onshore grid. The damping control method stabilizes the nearby synchronous generator by suppressing its frequency and power fluctuations.

Simulation studies were conducted using PSCAD V4.6 to verify the proposed control method. The simulation modelled the offshore wind farm as an equivalent three-phase current source that outputs constant power. Equivalent three-phase AC voltage sources modelled the AC/DC converters of the HVDC system. The rated power output of the wind farm, HVDC system, and synchronous generator are 500 MW, 500 MW, and 200 MW, respectively. The HVDC transmission distance is 100 km, and the rated DC voltage is 500 kV. The calculation time step was set to 20 microseconds.

The simulation conditions were set for a three-phase-to-ground fault on a circuit of the AC transmission line. The active power flow into the AC transmission line, the DC voltage and the active power output of the HVDC system were observed.

The simulation results showed that the HVDC system stabilizes the power flow into the AC transmission line by adjusting the active power output to suppress power oscillation caused by the grid disturbances.

The full paper will also propose a damping control method for power oscillation using the reactive power output of the onshore terminal of the HVDC system, and report the verification simulation results.

The growing penetration of inverter-based resources (IBRs) in modern power systems has raised significant challenges related to system strength and stability. Unlike traditional synchronous generators, which provide inherent inertia and short-circuit system strength, renewable sources such as wind and solar lack these stabilising characteristics, making networks more vulnerable to instability. Addressing system strength is therefore critical, but the exact requirements and methods of assessment remain uncertain.

Conventional electromagnetic transient (EMT) simulations are often employed to study small signal oscillations, but these are computationally intensive and not always necessary. An alternative is impedance-based frequency domain stability analysis, which characterises the interaction between system components by evaluating network impedance. This approach offers valuable insights into stability margins using the Nyquist criterion and is particularly effective for analysing power electronic systems. Although both synchronous machines and grid-forming (GFM) inverters are recognised as contributors to system strength, there is no generally accepted methodology to quantify their impact. This paper presents an impedance-based approach to assess the contribution of System Strength Mitigating Devices (SSMDs), focusing on small-signal stability. Three SSMDs; two GFM Battery Energy Storage Systems (BESS) and a synchronous condenser are compared, highlighting that stability support depends more on frequency response characteristics than nominal MVA short circuit capacity.

We study linear policy approximations for the risk-

conscious operation of an industrial energy system with uncertain

wind power, significant and variable electricity demand, and

high thermal output, as found in a modern foundry. The

system incorporates thermal storage and operates under rolling

forecasts, leading to a sequential decision-making framework. To

address uncertainty in key parameters, we formulate chance-

constrained optimization problems that limit the probability

of critical constraint violations—such as unmet demand re-

quirements or the exceedance of system boundaries. To reduce

computational effort, we replace direct uncertainty handling

with a parameter-modified cost function that approximates the

underlying risk structure. We validate our method through

a numerical case study, demonstrating the trade-offs between

operational efficiency and reliability in a stochastic environment.

As the complexity of our energy systems increases, cross-domain supervisory controller development gets increasingly difficult. In this paper, co-simulation is used to analyze supervisory control strategies for a multi-physics green hydrogen offshore wind turbine (GHOWT), including a multi-stack electrolyzer (mELY). For the cross-domain model composition, functional mock-up units (FMUs) are exported from various simulation platforms and executed in Python. We explore the operational characteristics of four rule-based energy management system (EMS) strategies while considering auxiliary component dynamics. The dynamics are important since in the off-grid application, fresh water needs to be produced by reverse osmosis and balance of stack units (e.g. pumps and heating) can only be operated by generated wind power. A case study with a 15MW wind turbine and three single electrolyzers (sELYs) is carried out over one week of turbulent power generation. Fresh water supply is only found to be limiting in the start-up phase with the chosen system configuration. The Equal distribution method with degradation feedback (EQx) is favorable considering all key performance indicators (KPIs) which are hydrogen production, energy use and degradation. Nevertheless, in all cases, excessive on-idle switching events cause uneconomic electrolyzer degradation, which is calling for optimized control approaches like model predictive control.

Existing publicly available models of future energy systems neglect power system stability. However, to ensure the reliability of future electricity systems, mapping stability and ancillary service needs is crucial. One key stability aspect is voltage stability. As a first step towards the modelling of future voltage stability-related ancillary services, we analyse the required reactive power compensation of the current grid. This work improves an existing grid model of the Nordic High-Voltage transmission grid based on open-source data with around 400 buses and performs power flow analyses for each hour in the reference year 2022. We evaluate the reactive power demands per bus to find the required reactive power compensation capacity for steady-state operation. We also analyse the available dynamic reactive power compensation from generation. For this, we use current grid code requirements for reactive power capabilities for generators. We also consider a scenario where STATCOM operation is required from all converter-connected generation. We further validate the model by analysing system losses and compare them with reported TSO losses. The work serves as a foundation for modelling voltage stability in the case of N-1 contingencies for future scenarios.

The increasing penetration of wind and solar generation necessitates efficient and reliable grid connection processes. A critical aspect of this process is the thorough testing and approval of the RMS and EMT models, which are typically developed by wind farm or solar park developers, often with the support of consultants. This paper presents the Model Test Bench (MTB), https://github.com/Energinet-SimTools/MTB, toolbox, an innovative open-source solution developed by Energinet, https://en.energinet.dk/, (the Danish TSO) in Python to significantly expedite the testing of these essential models for grid code compliance.

The MTB toolbox automates the execution of a suite of test cases and currently supports DIgSILENT PowerFactory for RMS models and PSCAD/EMTDC for EMT models. This automation reduces the manual effort and potential for inconsistencies associated with traditional testing procedures. The paper will provide a brief overview of the MTB toolbox's usage, illustrating how skilled engineers can leverage its capabilities to perform comprehensive set of test cases for grid code compliance assessments.

This paper will present several test cases demonstrating how the MTB facilitates the evaluation of adherence to the European Network Code (EU) 2016/631 on Requirements for grid connection of Generators (RfG), https://eur-lex.europa.eu/legal-content/DA/TXT/?uri=uriserv%3AOJ.L_.2016.112.01.0001.01.DAN Specifically, we will showcase its application in assessing critical performance aspects such as:

• Frequency Sensitive Mode (FSM)
• Limited Frequency Sensitive Mode - Over- and Underfrequency (LFSM-O/U)
• Reactive Power Capability
• Voltage Regulation Capabilities
• Fast Fault Current Contribution

with specific reference to the Danish Grid Codes for RfG, https://energinet.dk/media/zsxpqk5t/16_05118-127-nc-rfg-nationale-krav-for-nettilslutning-af-produktionsanlaeg-revision-3-01-04-2025.pdf

It should be noted that although the suite of test cases that can come with the MTB are specifically chosen to test for grid compliance against the Danish Grid Codes, they can easily be customized by simply editing or adding a row in the supplied “testcases.xlsx” Excel Workbook that is used as input to the MTB. Test cases are currently grouped into four Sheets, i.e. for:

• RfG cases
• Demand Connection Code (DCC) cases,
• Unit cases and
• Custom cases

For each test case, one need to specify the initial voltage (U0) and power (P0) setpoints, the P-and Q-modes the plant is operating in, and depending on the Q-mode, the related initial Q reference setpoint (Qref0). This depends on whether constant Q, constant Power Factor (PF) or Automatic Voltage Regulation (AVR) mode, sometimes also called Q(U) mode was selected. The MTB also allows for three Short-Circuit Ratios (SCRs) and their corresponding X/R ratios to be used for a test case. Typically, at maximum, minimum and at a level in between these two extreme values.

For each test case, up to 12 events can be specified. This includes:

• the event type,
• the time at which the event occurs,
• the new step value change, or
• the new ramp value change, e.g. a df/dt event

Currently supported event types are:

• A voltage change at the PoC (both step and ramp)
• A relative voltage change at the PoC (both step and ramp)
• A new active power (P) reference (both step and ramp)
• A frequency change at the PoC (both step and ramp)
• A relative frequency change at the PoC. (both step and ramp)
• A change in the grid impedance (SCR and X/R ratio)
• A new reactive power (Q) reference, based on the Q-mode of the plant (both step and ramp)
• SIPS or EPC signals
• Applied faults
• Phase jumps at the PoC
• Changes of custom signal (currently 10 supported)

The tool supports combinations of all event types in a single simulation case. Such as change in the grid impedance when a fault clears, representing properly the real scenario of a fault event.

While the MTB significantly automates test case generation and execution, the process currently still requires skilled engineers to visually inspect and evaluate the HTML, Plotly generated output results for grid code compliance. This also includes checking for consistency between the output of the EMT and RMS models. The test case examples that will be presented, will highlight the tool's effectiveness in streamlining the compliance verification process.

The open-source nature of the MTB toolbox, documented extensively on its Wiki, https://github.com/Energinet-SimTools/MTB/wiki, fosters collaboration and allows for continuous development towards further automation. Ultimately, the MTB toolbox offers a significant step towards accelerating the integration of renewable energy sources into the power grid by simplifying and standardizing the crucial grid code compliance testing phase.

　　In recent years, the integration of renewable energy and battery energy storage system (BESS) has been reshaping price formation in electricity markets owing to their distinctive roles. These technologies increasingly act as price setters (marginal units), thereby changing the structure of price formation. In the Australian National Electricity Market (NEM), market prices often turn negative when renewable generators are the price setters, and the frequency with which BESS acts as a price setter has risen markedly in recent years. To analyse these developments more precisely, this study introduces a new decomposition framework.

　　We define three metrics—Negative Incremental Cost (NIC), Offset Incremental Cost (OIC), and Core Incremental Cost (CIC)—to decompose price formation with respect to an additional 1 MW of demand. NIC represents the total incremental cost associated with negative incremental supply, OIC represents the total incremental cost of the least-cost offset of this negative supply, and CIC is the residual cost. In addition, contribution rates (CRs) are defined to compare the contributions of different units and fuels to CIC. This framework clarifies the role of price setters when negative incremental supply occurs, a situation not explicitly treated in previous studies.

　　Applying these metrics to NEMDE Price Setter data from 2021 to May 2025, we find that deviations of market prices from core price setters’ bids occur predominantly around zero prices. NIC plays a critical role in these deviations, although OIC can partly offset it. Solar and wind frequently appear in NIC, and their negative bids sometimes lead to positive NIC contributions, exerting upward pressure on prices. By contrast, BESS charging on average plays a role opposite to that of solar and wind, contributing negatively to NIC and thereby exerting downward pressure on prices.

　　Further results show that the contributions of solar and wind to CIC increase over time, while those of conventional fuels decline. Analysis of NIC occurrences also indicates that the proportion of positive NIC is consistently substantial, mainly due to solar and wind, while the increasing appearance of BESS is also observed.

　　Overall, the decomposition into NIC, OIC, CIC, and CRs provides a novel perspective for examining the mechanisms of price formation in the NEM. The results reveal counter-intuitive upward effects of negative bidding by renewables, whereas BESS tends to behave in the opposite direction, particularly through charging. These findings suggest that renewable energy and BESS is playing a growing role in shaping price formation, though the precise nature of this role requires further investigation.

Rajasthan is the largest state in India by area and has the highest renewable energy (RE) potential in the country, estimated at around 450 GW (solar and wind combined). The state aims to install approximately 95 GW of RE capacity towards the national target of 500 GW by 2030. The transmission network plays a vital role in integrating and evacuating power from the generating stations to the load centres. Since a transmission infrastructure has a significantly longer gestation period than that of RE projects, the transmission network needs to be planned well in advance to prevent curtailment of power generated from RE sources due to network unavailability. In this context, our paper examines the transmission network availability in Rajasthan to integrate the power generated by the proposed RE projects and meet the projected state demand for the financial year 2029-30. Our study modelled the transmission network at voltage levels of 220 kV and above, using the PSS/E software, and executed load-flow analysis to evaluate the network’s availability to accommodate the increasing RE-based power generation in the state. The study identified the network constraints and also estimates the investment required to execute the recommended network strengthening measures.

The spread of e-mobility can be accelerated if private charging infrastructure could be put to wider and more flexible use. Technical and tax restrictions currently prevent the simple and seamless charging of different users or different cars at private charging points in Germany. In this paper, we present a new technical solution for the separate metering and billing of EV-charging at private charging points. Our solution is based on an advanced smart meter infrastructure and event-driven tariffs. At the beginning of each charging process, the charging infrastructure triggers a tariff event to allocate the electricity consumption to the specific tariff register of each user or EV. The accumulated energy quantities of each user are then transmitted to the electricity supplier using standard and secure BSI-processes. The paper describes the technical framework, including the enhanced smart meter infrastructure, and the required processes and signalling between the stakeholders and technical components. Results of various tests using a prototype of an enhanced SMGW of EMH metering conducted in our E-Mobility Laboratory are also shown.

In recent years, wind energy integration into power systems has grown rapidly, reaching 1,136 GW of installed capacity in 2024. As wind power penetration increases, maintaining power system stability under grid disturbances becomes critical. This requires dynamic models capable of simulating wind turbine behavior during transient events—such as voltage dips—while also being generic enough to avoid violating manufacturers' non-disclosure agreements.

The IEC 61400-27 standard provides a solution by defining technology-neutral models that accurately represent wind turbines regardless of manufacturer. However, these models have been mostly implemented in proprietary software, which hampers collaboration between companies and academic institutions using different platforms. This paper demonstrates how Python can be used to openly simulate wind turbine models, enabling broader collaboration across the industry and academia. Specifically, the work focuses on implementing a doubly-fed induction generator (DFIG) wind turbine model based on the IEC 61400-27 standard in Python, and comparing its simulation results with those from DIgSILENT PowerFactory, a leading proprietary tool in power system analysis. Results confirm that the Python-based model achieves equivalent accuracy, validating its use for open-source power system studies.

The development of the IEC 61400-27 standard began in 2009 due to the lack of generic wind turbine models. Its first edition, released in 2014, introduced standardized models for turbines and wind power plants, including validation methodologies. A revised version was published in 2020 after extensive consultation with grid operators, manufacturers, and researchers. Yet, adoption has been mostly limited to closed-source environments, creating challenges for validation and collaborative development. In power system simulation, tools such as PSCAD, PowerFactory, PSS/E, and MATLAB Simulink are commonly used but are not open-source, limiting interoperability and information exchange. This highlights the need for open alternatives capable of accurate dynamic simulation. In this context, tools like Collimator—an open-source, high-performance simulation suite built around Python—are emerging. It supports block diagram modeling and seamless integration with other Python-based power system analysis modules.

In this study, a DFIG wind turbine model was implemented in both Python and PowerFactory. To compare them, simulations were run using three voltage dips with different residual voltages and duration under full-load and partial-load conditions. The results from both tools showed strong agreement, validating the Python implementation’s accuracy.

In conclusion, the IEC 61400-27-based wind turbine model implemented in Python delivers results equivalent to those from DIgSILENT PowerFactory. This supports the use of Python as a viable open-source platform for wind turbine modeling and simulation, promoting greater collaboration and model sharing among researchers and industry stakeholders.

The rapid expansion of renewable energy, particularly offshore wind power in Europe, is set to reshape the continent's power system, transitioning from a rotational mass-based inertia backbone to IBR entities. This inevitable shift highlights the critical need for sophisticated system stability analysis incorporating simulation models from manufacturers to facilitate such studies effectively, that in turn invokes the need for standardizing the interface of simulation models across manufacturers to address compatibility problems associated with the use of different compiler versions and software architecture, confidentiality problems, as well as accuracy and reliability issues in grid interconnection studies, which becomes even more crucial in complex multi-vendor environments. These projects demand simulation frameworks that can seamlessly integrate diverse components while maintaining accuracy and scalability, addressing challenges such as system stability, fault handling, and performance optimization. On the subject of simulation, the effective and less expensive solution for majority of the interaction studies remains so-called offline simulation (such as PSCAD, DIgSILENT PowerFactory, EMTP). In addition, the need for real-time simulations based on replicas to is key to obtain more realistic test results, embedding the out of sight stochastic dynamics introduced by control and communication systems. In this paper, we first highlight the trend towards multi-vendor energy projects, the resulting complexities and issues, and the required adaptation for stability analysis with offline and real-time simulations. This work underscores the need for high-quality models and explores the challenges with the evolving transition and requirements from three vertices of manufacturer, grid operator and test laboratory. We explore the pressing need for multi-vendor simulations, with a focus on offshore wind power. We elaborate on OEM experience with implementation of one simulation tool independent interface, model usage by test laboratory and grid operator to derive key lessons learned from both the challenges encountered, and the innovative solutions adopted. The collaboration between OEM, test laboratory and grid operator illustrate how standardized model interfaces can reduce project timelines and improve the quality of interconnection studies.

The growing adoption of battery electric vehicles demands efficient and flexible solutions for bidirectional charging to support both grid-oriented applications and emerging business models. This Paper presents an open-source-based test bench designed to investigate and evaluate charging and discharging strategies. The setup is based on standardized hardware and software, offering modular expandability and providing interfaces for integrating various backend and energy management systems. This enables reproducible testing and comparison of different scenarios, ranging from grid-stabilizing applications to user comfort–oriented strategies. The goal of this approach is to accelerate the development of bidirectional charging methods by fostering transparency and reproducibility, thereby creating a shared research foundation for both industry and academia. Initial evaluations have demonstrated that the test bench serves as a reliable platform for validating strategies in the context of Vehicle-to-Grid (V2G) and Vehicle-to-Home (V2H) applications. To present the chances of this test bench, a bidirectional P(V) characteristics curve is evaluated.

The Balancing Mechanism (BM) is the main tool for keeping electricity supply and demand balanced in Great Britain, while respecting network constraints. Between April 2022 and March 2025, its costs were £2–3 billion per year, prompting participants to call for more efficient dispatch and greater transparency. To help meet these needs, the article presents BMViewGB, an open-source, map-based visualisation tool that displays the spatial distribution of BM costs and volumes. The straightforward map layout is designed for users with varied professional backgrounds and can also act as a foundation for further research, such as the development of digital simulators of the Balancing Mechanism.

Quantifying the energy supply potential of company fleets as part of implementing bidirectional charging systems for electric vehicles is crucial for future grid planning. Bidirectional charging has two key advantages. Firstly, it allows optimised load control and, secondly, it enables the provision of electrical energy e.g. back to the power grid. The introduction of the technology thus presents a significant opportunity for companies with large vehicle fleets, such as bus operators, city cleaning services, and logistics companies, to optimise their energy demand from the grid and provide ancillary services. Especially fleet operators with scheduled routes and repetitive charging patterns offer charging windows where the time that an electric vehicle is plugged into a charging station can be used to shift, as well as reduce the electrical load, or even to discharge the vehicle and still fulfil the requirements for the next trip. Furthermore, in the event of a power outage, energy from a fleet could be made available in order to ensure the continued functionality of critical infrastructure.

To realise the potential, profiles of company fleets of the total energy stored and the energy that can be released at different times without affecting the normal operation of the company are required. This information is not directly accessible and must be calculated or estimated using data from different systems.

Therefore, the study presents an analysis of the charging behaviour observed among different fleet operators, in addition to a methodology for calculating the available energy profile over a period of one week, with a precision of 15 minute intervals. Open Charge Point Protocol (OCPP) data from a Charge Point Management System (CPMS) combined with data from a fleet management system is used to develop the energy supply profiles. Four divergent information states are taken into account. In the simplest case, a charging process is carried out at a DC charging point, providing information on the vehicle's state of charge. The amount of energy stored can then be calculated at any time using the vehicle's authentication token or the vehicle's battery information stored in the fleet management system. However, if the charging process takes place at an AC charging point where no information about the state of charge is transmitted and no assignment to the vehicle or battery capacity is possible, a method based on historical charging patterns is required. To validate the developed methodology, data from three different fleet operator types are analysed, the different information states are evaluated and the possible inaccuracy of the individual methods is assessed.

The aim of the study is to provide grid planners, companies, and policymakers with a method to evaluate the potential of company fleets for grid services. The realization of a smart grid aims to maximize electromobility potential, promote data-based decision-making, and make grid expansion more efficient. The study offers valuable insights into integrating electric vehicles into the energy system and their role in the energy transition.

Achieving interoperability in multi-vendor HVDC systems is a key enabler for the efficient integration of offshore wind power into the European grid, supporting the EU’s objective of climate neutrality by 2050. This session will begin with a brief overview of the InterOPERA project's objectives and main challenges. It will then present the real-time demonstrator and outline the proposed approach for defining both overall system and subsystem technical specifications. These specifications translate predefined functional requirements into practical terms, supported by HVDC grid design studies based on generic models. This work highlights the urgent need for a structured process and clear assumption-setting to support effective pre-tender planning studies.

Accurate modeling of wind turbines requires precise power curves, which often remain unavailable for innovative turbine technologies, prototypes, or undocumented plant configurations. This study develops a data-driven methodology for generating synthetic power curves that serves as a foundation for advanced energy system analyses and wind farm planning. Based on 509 quality-filtered real power curves, we develop a two-stage approach that creates weighted reference curves from similar turbines and subsequently applies physically-based scaling via specific power density. Our methodology achieves an RMSE of 2.14\% with global training data and up to 1.27\% with manufacturer-specific data, representing significant improvements over established physical methods (Sørensen 4.56\% RMSE, Saint-Drenan 2.37\% RMSE). The consistent performance across all technology segments from 150--650\,W/m$^2$ specific power density enables precise applications in energy system modeling, grid planning optimization, and economic evaluation of wind energy projects. This foundational methodology can continuously expand with new market data, thus providing a robust basis for complex energy system analyses and future scenarios.

Considering the increasing usage of electric vehicles, the possibility to utilise their extensive combined energy storage within our power grids to increase system flexibility and reduce emissions is becoming a promising area of research. We present a holistic approach for the optimization of district energy systems considering heating, electricity and mobility. Specifically, this optimization maximizes the self-consumption and minimizes the peak load. This work extends on previous studies by integrating mobility into district energy management, applying stochastic programming methods to a linear optimisation framework, and through using an interface to obtain data from real world vehicles for district energy management. Mobility data is created with a chain of three tools: TAPAS (Travel and Activity PAtterns Simulation) and SUMO (Simulation of Urban MObility) for computing daily trip data (e.g. time, duration, energy consumption), and CHARGIN (Consumer Habits based Approach to model Recharging and Grid INtegration). By using residential presence times from the mobility dataset, we determine electricity and heating load profiles with Modelica. Integrating mobility data with the Load Profile Generator (LPG) enables the creation of synthetic, high-resolution load profiles through agent-based behavior simulation that accurately reflect home occupancy. In order to account for natural behavioural variability, we employ a stochastic programming approach using multi-scenario simulation methods. We show how to include such stochastic programming methods into the linear optimisation framework oemof (open energy modeling framework). The holistic energy systems optimization is done with the tool MTRESS (Model Template for Renewable Energy Supply Systems). This tool manages the charging and discharging flows of the EV batteries for the system optimisation. This scenario-aware method can be utilized to plan energy systems that consider uncertainties associated with varying demand profiles, providing a more robust and flexible approach to energy planning. Another novelty of this work is the integration of data from real electric vehicles in the district energy management system. The sensor data transfer is achieved using a standardised V2X module. We investigate how this data can be used to improve the district energy management system and as a direct input for the simulation models. This district level simulation with integrated energy, heat and mobility energy flows is a stepping stone towards the simulation of a district level energy model.

For effective parallel operation with existing systems, it makes sense for grid-connected systems to fulfil the requirements placed on converters in accordance with VDE-AR-N 4105 as precisely as possible. This also includes static voltage support, which makes it possible to counteract the voltage increase caused by feed-in and to significantly increase the absorption capacity of distribution grids for decentralised energy systems. This motivates the investigations published here in the “Fuchstal-leuchtet” and “Verteilnetz 2030+” projects as to whether grid-forming systems are also capable of implementing the static voltage support methods in accordance with VDE-AR-N 4105. This is a major challenge, particularly due to the fact that grid-forming systems directly influence the voltage. In a previous work, the ability of a grid-forming inverter to realise a Q(V) characteristic curve in a laboratory environment in parallel operation with a grid-following inverter has already been demonstrated. In this work, the dynamic interactions of the two inverters are considered. This includes different start-up time constants of the Q(V) control and varying positions of the inverters in the grid. In addition, the reaction to rapid voltage changes is analysed

Power cables are a critical component of offshore wind farms, and their design and rating are often based on conservative assumptions regarding installation methods, environmental conditions, and cable losses. This conservative approach coupled with a lack of trusted risk mitigation tools frequently leads to oversized and costlier cables, leaving substantial optimization potential untapped.

This paper introduces the Unitech Cable Load Prediction System (CLPS)—an advanced tool developed to enhance the design and operational efficiency of power cables. CLPS integrates a Finite Element Method (FEM)-based digital twin with calibration capabilities using Distributed Temperature Sensing (DTS) data. Currently deployed on a 300 km High Voltage Direct Current (HVDC) trading link, the system is already demonstrating improvements in operational efficiency and revenue generation.

In the context of offshore wind farms, CLPS offers significant value in risk management and cost reduction, particularly through the potential downsizing of conductor cross-sections. The paper presents validation results from the operational HVDC system and simulation studies on a model wind farm. These simulations illustrate how CLPS can effectively manage thermal risks, reduce investment costs, and minimize curtailment losses.

Furthermore, the paper outlines the iterative design process of cable systems for offshore wind farms, showcasing how CLPS supports informed decision-making. By simulating the operation of a representative wind farm, the study highlights the system’s impact on cable sizing, cost savings, curtailment losses, and the management of uncertainties related to thermal resistivity and ambient conditions.

As the penetration level of renewables grow, managing, balancing and keeping enough reserves on the grid offers challenges. Part of the solution, currently being implemented in many electricity markets, is the participation of traditionally non-dispatchable renewable energy to balancing services. Active participation of wind power requires accurate minute to hour-scale forecasting. Similar forecasts are crucial to understand the constantly varying need for activation of balancing services to meet departures from production plans. As input to such forecasts, power measurements taken at wind farms are insufficient on their own because their absence in above cut-out (full load) or below cut-in (no production) cases. In both cases, power data fails to indicate forecast trends or biases, which may stem from e.g. high winds or icing. Additionally, in curtailed operation power measurements does not inform on the potential power. Because of this, wind farms should ideally be complemented with independent wind measurements.

With hub heights now exceeding 200m (even 300m in low-wind areas), traditional met masts are inadequate due to costs and required planning permission. Remote sensing tools like SODARs and LIDARs are better suited, offering real-time wind profiles and turbulence data.

However, deploying these instruments in new environments poses challenges:

• Reliability: How is predictability impacted when the data stream is lost?.
• Handling of missing data : When data gaps appear in the observations, what alternatives are there?

To address impacts of weather-related and real-time gaps on forecasting challenges as well as data quality issues, we use the 75-member WEPROG MSEPS ensemble NWP, matching forecasts to recent observations in time and space.

NWP-Measurement Mismatch

NWP models use grid cells, while sensors provide point data—creating a resolution gap. Additionally, NWP models traditionally run hourly, while sensors update in seconds/minutes. We use cross-wavelet analysis to map how phase errors, amplitude errors and resolution differences contribute to the forecast error in time. The analysis is used to study if higher-resolution NWP models at sites with met masts, SODAR, and LIDAR can improve alignment.

Verification Challenges

High-resolution systems are costly, and traditional metrics (MAE, RMSE, etc.) often fail to show clear benefits. With a rule-based skill score matrix we can evaluate different event types and setup phase-error tolerance, measuring both detection predictability and model performance.

The motivation behind the work is the desire to operate wind farms proactively, understand the weather conditions at the wind farm and facilitate participation on intra-hour balancing markets. In line with that aim, we focus on the theoretical benefits and challenges of independent site measurements of wind speed to forecast the available power and investigate skill improvements in forecasts of wind energy and compare the use of remote sensing to traditional met masts.

The accelerated electrification of industrial processes is raising demand for stationary battery storage whose raw‑material needs, life‑cycle impacts and cost trajectories differ markedly between technologies. While lithium‑iron‑phosphate (LFP) systems currently dominate, sodium‑ion batteries (SIB) are emerging as a promising alternative in the past years, particularly in Europe, thanks to their broader raw‑material base and potential cost advantages [1,2]. This study shows an agent‑based model (ABM) to quantify how techno economic; social and policy drivers shape the relative attractiveness of both technologies. A global sensitivity analysis pinpoints the factors that most strongly steer adoption, providing guidance for industrial decarbonisation strategies. The ABM compares LFP and SIB through distinct cost‑ and performance learning curves, raw‑material price trends and recycling assumptions. In the ABM two thousand heterogeneous industrial firms (Agents) are investigated in Terms of their investment decision making behaviour based on the factors capital costs, risk preferences and how the individual agents are influenced by other agents and broader social environment. Key inputs, including CAPEX/OPEX ranges, supply‑chain risk indices, CO₂‑price signals and subsidy levels, are varied simultaneously. A variance‑based sensitivity analysis identifies the parameters and interactions that drive changes in adoption share, net present value and payback time. Policy signals, supply‑chain considerations and social diffusion are expected to influence technology choice more strongly than cost learning alone. Rather than delivering point forecasts, the model offers a transparent open-source framework for exploring leverage points, economic, regulatory and social, that could foster a diversified and more resilient battery portfolio on the path to industrial decarbonisation in Europe. [1] Bielewski, M., Pfrang, A., Quintero Pulido, D., Bobba, S., Georgakaki, A., Letout, S., Kuokkanen, A., Mountraki, A., Ince, E., & Shtjefni, D. (2023). Battery technology in the European Union — 2023 status report on technology development, trends, value chains & markets (EUR 31698 EN). Publications Office of the European Union. https://doi.org/10.2760/52259

[2] Yao, A., Benson, S. M., & Chueh, W. C. (2025). Critically assessing sodium-ion technology roadmaps and scenarios for techno-economic competitiveness against lithium-ion batteries. Nature Energy, 10, 404–416. https://doi.org/10.1038/s41560-024-01701-9

Battery energy storage system (BESS) investors typically seek grid connections at locations determined by non-grid factors

such as land availability, creating potential mismatches with optimal grid integration points. Compounding this challenge, tra-

ditional hosting capacity assessments rely on conservative worst-case scenarios that significantly underestimate viable BESS

capacities and reduce investment attractiveness. This paper presents a Multi-Period Quadratic Constraint Optimal Power Flow

framework for one-year hourly operations that evaluates cooperative investment models where investors grant operational control

to distribution system operators, enabling mutual benefits through larger installations and optimized grid operation. The convex

optimization leads to fast solving with approximately 160 seconds. The methodology integrates state-of-charge temporal depen-

dencies, degradation costs, and penalty terms to model comprehensive BESS operation while enforcing voltage, thermal line,

and power balance constraints. Applied to the CIGRE MV benchmark network with 2024 market data, the framework system-

atically compares standalone arbitrage operation against grid-integrated scenarios through Net Present Value analysis. Results

identify an optimal BESS capacity of 30 MWh at a single connection point, with network bottlenecks limiting further capacity

expansion. Although line congestion hours increase substantially as capacity grows, the configuration remains economically at-

tractive, demonstrating that cooperative operational frameworks unlock significant value for both investors and grid operators

while maintaining system reliability.

Stability is an essential property of a dynamic system. While it is highly desirable to prove stability analytically, this is a challenging task, especially for non-linear systems. Although Lyapunov's stability theory provides a comprehensive basis for systems with non-linearities, the actual application of the theory is unclear. This is due to the difficulty of finding a Lyapunov function with the required properties. This work presents an approach to deduce a candidate Lyapunov function from a Hamilton representation of the system, which is a special structure of the systems's differential equations.

The methodology is applied to two connected grid-forming inverters with droop controls and is successful for a simplified version of the system. Then, efforts are being made to extend the procedure by including the transmission line losses. However, this step increases the complexity of the investigation and poses challenges that prevent clear results.

Landsnet, the Icelandic TSO (Transmission System Operator), maintains and operates the transmission system in Iceland. The system is isolated from other transmission systems, supplying electric power to the Icelandic society. Approximately 80% of the load is steady power intensive customers (aluminium smelters, ferrosilicium plants and data centers). The generated energy is entirely renewable, 75% hydro based and 25% utilising geothermal power. The present transmission system is fully exploited, thus not capable of handling proposed large-scale integration of wind power and associated increase in consumption (e.g. electrolysers). Therefore, Landsnet started a research project with the goal to provide a roadmap towards a „target grid“ for 2050+. The project will, as well, provide guidance for a safe and firm integration of wind power into an isolated and weak transmission grid and highlight the necessary requirements for feasibility studies. In Phase I a tool has been developed for assessing the impact of wind variability on the transmission system which allows identification of stress points, assessment of variability impacts on individual lines and transformers, and provides a statistical and visual basis for planning mitigation measures. The results from Phase I will provide valuable input to proceed to Phase II for further modelling and simulations.

Phase II is the main system modelling and simulation part of the project. Based on the results from Phase I, wind integration scenarios will be defined and possible grid solutions modelled and simulated. The solutions will comprise grid enhancements (new grid components and reinforcements, increased meshing), new technology (STATCOMs, synchrocondensers, storage, grid-forming converters etc.), market solutions (e.g. flexible consumption) etc.

The share of weather-dependent renewable energy is rising as European power grid balancing markets move toward greater

unification. In the Nordics, proactive and automatic balancing using manual Frequency Restoration Reserves was implemented

in March 2025, a prerequisite for joining the European balancing platform Manually Activated Reserves Initiative.

This paper investigates data from Sweden following its automatic balancing implementation to determine if the challenge of

maintaining grid stability correlates with synoptic circulation types. For this study, the challenge of maintaining grid stability is

quantified by the absolute error of the imbalance forecast algorithm within the new system. Circulation types are computed using

the automatic Jenkinson-Collison classification scheme based on atmospheric surface pressure signals.

A regression analysis establishes circulation types as a statistically significant driver of absolute imbalance forecast errors and

reveals that balancing is more challenging under cyclonic flows and those originating from the north-westerly quadrant. A control

study highlights wind speed as the most dominant underlying parameter. However, accounting for wind speed does not remove

all influence of the circulation types, demonstrating that they act as a proxy for complex weather dynamics that affect imbalance

forecasting.

Bidirectional charging holds significant potential for integrating renewable energy and reducing system costs in Europe’s energy transition. However, these benefits only materialize when electric vehicles actively participate in Vehicle-to-Grid (V2G) applications rather than solely optimizing self-consumption via Vehicle-to-Home (V2H). In Germany, state-induced price components – especially grid fees – continue to hinder the economic viability of V2G. While taxes and levies are being addressed, grid fees remain a barrier to intermediate storage of grid electricity. A blanket exemption would unfairly shift costs to other users. With this paper, we explore Flexible Connection Agreements (FCAs) to ensure grid-neutral charging and discharging, enabling targeted reimbursement of grid fees. Using our GridSim model, we assess grid load, energy subject to charges, and expansion costs across use cases. We also implement an envelope concept to temporarily limit charging processes and reduce grid impact. Our goal is to support the intelligent, scalable design of FCAs and contribute to reforming grid fee structures. This would incentivize system-friendly flexibility from mobile storage systems while ensuring fair cost allocation and preserving viable business models

This paper investigates the feasibility of implementing the newly proposed PRNB (grid security-based primary control) requirements in state-of-the-art grid-following inverters. While current LFSM (Limited Frequency Sensitive Mode) specifications primarily define static droop characteristics, they lack stringent dynamic performance criteria. With the increasing share of inverter-based generation and decreasing system inertia, faster and more predictable frequency response is essential for grid stability.

A laboratory-based test bench was developed to evaluate the dynamic response of a commercially available 6 kVA PV inverter under both existing VDE-AR-N4105:2018 guidelines and the proposed PRNB requirements. Using a real-time simulator and systematic parameter variation, the inverter’s frequency-dependent active power response was measured and calibrated against PRNB boundary curves.

Results show that the tested inverter significantly outperforms current LFSM requirements and, after parameter optimization, can meet the tightened PRNB dynamic specifications without compromising stability. These findings confirm the technical feasibility of PRNB-compliant behaviour in existing hardware and provide a basis for refining future grid connection standards.

To effectively design a future energy system where wind power plays a major role, it is essential to represent wind generation using accurate time series data in the modelling process. For pan-European applications, the data must represent the significant geographical variation in wind resources across Europe. This is important for modelling current wind installations and for analysing the economically efficient deployment of new installations throughout Europe. And for analysing and comparing onshore vs. offshore wind installations in scenarios towards 2050 and beyond, the data must include accurate wind generation time series for both, including new technologies. For a wide-spread use of the data, also outside of academic research, it is essential to have the data validated.

This paper discusses findings from several projects (EU, Nordic and Danish), where the aim has been to provide representative high-resolution wind generation time series for pan-European power and energy system studies. Recent updates to the wind modelling focus on detailed wake modelling, stochastic simulation of unavailability and considering the impacts of climate change. A key result where the presented modelling is applied is the Pan European Climate Database (PECD) version 4.2 dataset for The European Network of Transmission System Operators (ENTSO-E). The data are made openly available in the C3S Climate Data Store. The generated data include also other technologies, such as solar photovoltaic, but here we focus on wind power.

The results highlight the need for adjusting reanalysis and climate projection wind speeds with a high resolution wind dataset, such as the Global Wind Atlas (GWA). We find that GWA version 2 (GWA2) improves validation metrics (correlation to measured data, capacity factor, etc.) across Europe compared to using ERA5 reanalysis wind speeds directly. GWA3 appears to be less effective than GWA2. A relatively detailed wake model, considering plant size, turbine spacing, appropriate turbulence intensity, etc., provides more accurate results than simpler setups. Stochastic simulation of unavailability provides more accurate representation of wind generation distribution especially at high generation. We discuss the impacts of the improvements on power and energy system modelling.

The same level of modelling detail as used with reanalysis data (covering 40+ years), is applied also when working with climate projections towards 2100. Overall, the impact of climate change on pan-European wind generation is expected to be low-to-moderate based on the results.

While the generated base pan-European datasets are hourly, the developed wind model allows simulation at up-to 5 min resolution. Sub-hourly simulation capabilities are expected to be increasingly in demand as markets move to higher resolution (15 min or even 5 min). With growing focus on intra-day and balancing markets—largely influenced by forecast inaccuracies—there is a rising interest in simulating wind forecasts, not just available power, for future scenario analyses. And as more-and-more offshore wind power plants are built close to each other, there is increasing need to model large-scale wakes in detail. We discuss plans for considering these aspects in our ongoing and future work.

The electrification of transport is a cornerstone of Germany’s energy transition, with electric vehicles (EVs) offering both decarbonization benefits and challenges for distribution grids . From 2025, § 41a of the Energy Industry Act (EnWG) will mandate that suppliers provide dynamic tariffs indexed to wholesale prices, complementing § 14a EnWG on load-dependent network charges. These regulatory measures aim to incentivize demand flexibility, yet their economic impacts on household EV charging remain unquantified. This study evaluates four charging strategies (uncontrolled, market-driven, smart, and bidirectional) from a household perspective. Using a mixed-integer linear optimization framework and using dynamic electricity prices, time-variable grid fees, and mobility profiles. Results show that uncontrolled charging under fixed tariffs produces the highest costs, while smart charging significantly reduces expenses and bidirectional enables negative net electricity costs under favourable conditions. Seasonal differences further highlight that winter price volatility increases both savings potential and exposure to cost variability. Overall, the findings suggest that dynamic tariffs and grid fees can enhance the economic case for smart and bidirectional charging, but their effectiveness depends on consumer acceptance and infrastructure availability.

This is an abstract proposal for 2 presentations that have a dialogue in presenting, and a joint paper.

IEA TCP WIND Task 25 ”Design and Operation of Energy Systems with Large Amounts of Variable Generation” compiled Recommended Practices for power system impact studies, what has traditionally been called wind and solar integration studies. This provides research institutes, consultants, and system operators with the best available information on how to perform an integration study. It is also useful in benchmarking any integration studies: the recommendations check list can be used to mark what has and has not been taken into account. The latest update, to Edition 3, includes recommendations for very high shares of wind and solar – wind and solar dominated power systems, with energy system coupling. It is based on more than 10 years of work within the International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) Task 25: Design and Operation of Power Systems with Large Amounts of Wind Power and the IEA Photovoltaic Power System Programme (PVPS) TCP Task 14: High Penetration of PV Systems in Electricity Grids.

The Recommended Practices contain the following sections: Input data; Scenario set up; Adequacy; Operational impacts; Dynamics; Analysing and presenting the results. Each section highlights the issues with the main recommendations, for small/medium wind and solar shares in the power system and also for wind and solar dominated systems.

Following the presentation of Recommended Practices checklist there will be a dialogue on how this has been taken into account in a case study investigating electrification of industry and transport in Sweden. Sweden benefits from a carbon-neutral electricity system composed by hydropower nuclear power and wind power. However, with a large energy-intensive industry, including iron and steel as well as petro-chemical industry, which need to move away from fossil-fuels the electricity demand is expected to double.

To analyse the changes in the electricity and energy system that electrification of the industrial and transport sectors entails, a large geographical range is required to capture trade flows and a long time horizon that reflects changed conditions for investments in new electricity production and storage with associated infrastructure over time. At the same time, a high geographical resolution is needed to represent transmission constraints in the electricity grid and a high time resolution to capture the variability of weather-dependent electricity production. To cope with this, the analysis in is based on three different electricity system models in combination; a European investment model to study the development of the electricity system based on today's capacity mix up to the year 2065 followed up by calculations with an investment model with high geographical resolution for the Nordic electricity system from which results are used to calculate flows of active and reactive power in an electricity grid simulation model and to check that the calculated electricity systems are physically and electrically reasonable in normal operation and to identify the need for reactive power compensation.

We will go through the different modelling choices made in the study, relate them to the recommended practises, discuss the implications on results and future work.

The amount of converter connected production continues to increase in the Finnish power system. Most of the new production is wind power which is concentrating on the 400 km long area in the western coast of Finland. This area currently has more than 5 GW of wind power and very little load or synchronous generators, creating issues with converter-driven stability.

The studies on converter-driven stability and the required mitigation methods and actions are mostly based on the wide area electromagnetic transient (EMT) simulation studies. To verify and improve the accuracy of these models, Fingrid planned a real-life grid test where converter-driven instability was planned to be evoked intentionally by reducing the network strength in a limited area in the western coast.

In the grid test the converter-driven instability was successfully evoked in a controlled manner. The voltage oscillations measured during the test match relatively closely with the oscillations observed in the simulation models. This confirmed the capability of the simulation models to replicate the response of the converters in a realistic manner, and the data received from the test results could be used to further enhance the accuracy of the simulation models.

Curtailment of wind and solar energy is seen as one of the most important issues in some countries, and will be an even bigger problem in future electricity systems that use large amounts of renewable energy. International cooperation under the scheme of the International Energy Agency's (IEA) TCP (Technical Cooperation Programme) Wind Task 25 (Design and operation of energy systems with large amounts of variable generation) and its continuation task, Task 63, has been investigating the global situation of wind and solar curtailment for more than a decade.

Curtailment is not necessarily a bad thing, as it may increase the potential for flexibility, such as upward reserve from wind and solar power, but excessive curtailment may have a negative impact on the business interests of power producers and the rapid implementation of renewable policies,

The meaning of curtailment has changed in the past and is likely to change in the future. The technical reasons for curtailment can be divided into three categories: local network constraints, system-level curtailment and energy surpluses, although few countries provide statistics that distinguish between these reasons. Furthermore, in some countries, negative prices in the spot market create ‘voluntary curtailment’ or ‘economic curtailment’ as a market behaviour. The statistical data published in some countries do not distinguish between forced curtailment by TSOs and the market-based ‘economic curtailment’.

This paper includes four topics;

1. rethinking and redefining curtailment

2. proposing for unified statistics on curtailment

3. updating curtailment statistics in various countries/areas

4. surveying and summarising future curtailment estimates in various country/areas.

Specifically, the paper reviews previous publications and discussions on curtailment and rethinks the definition of curtailment. It will also make recommendations to governments, regulators and system operators around the world for uniform statistics on curtailment. Although many papers and reports on estimating future suppression have already been published in various countries and areas, reviewing and summarising these methodologies and results will help to reduce the uncertainty caused by curtailment and help to ensure efficient operation and use of flexibility in future power systems and energy systems.

Degradation of system strength because of inverter-based resources (IBRs) is a major concern facing the zero-carbon transition. Blackouts like the one in Iberia on April 28 highlight this. They are generally followed by:

- Uninformed conservative voices calling for an end to investment in renewable energy;

- Optimistic solar and wind power advocates claiming that IBRs were not the problem and can totally replace synchronous machines;

- Transmission system operators requiring new investments in synchronous compensators.

This paper will attempt to inform the debate and explain clearly why synchronous machines cannot be totally replaced. At the same time, this does not mean that investment in renewable energy should end, nor are new investments in synchronous compensators the economic way forward.

The author has previously presented work on Type 5 wind turbines, i.e. those that drive a synchronous generator, without inverters, through one of three variants of hydraulic variable speed system. In their 2024 paper he and co-authors presented to this workshop, they explained that the SyncWind Type 5 power-train is the most cost-effective and proven of these three. This paper will detail the various control sub-systems of the power-train, to enable high-level comparison of its control systems with the IBR approach to grid-forming.

The Draghi report on EU Competitiveness from September 2024 states that regional planning needs to be strengthened, with reference to differences between European regions and considering a ‘one-size-fits-all’- solution unrealistic. Regional synergies are expected to ameliorate challenges and contribute to an acceleration of infrastructure projects, thus bringing European decarbonization and energy security a step further.

To deliver on this need, Northern Seas Transmission System Operators (TSOs) for electricity jointly studied an economically efficient and viable way forward for offshore infrastructure for the 2040 time-horizon. The approach focuses on identifying a promising set of offshore hybrid interconnection projects, as this special cross-border-project-type requires close collaboration across multiple borders. Collaboration relates not only to technical questions, but also to financing and potential cost-sharing across the sea basin. Discussions on the latter have intensified after the European Commission published their guidance on this topic in summer 2024.

The Northern Seas TSOs wish to provide a useful basis for joint discussion between the region’s governments and TSOs. Thus, joint planning builds on and complements existing Pan-European- and national plans, testing a variety of potential options. After a short description of the methodology applied, two example topologies are presented and discussed.

“Grid codes increasingly demand WPPs to contribute dampening inter-area oscillations. A key performance indicator for the damping effect is the phase shift between grid voltage oscillation and the plant reactive power output, called POD-Q response. POD-Q should be coordinated with other control modes, particularly existing voltage control. That coordination is done either in continuous mode or discontinuous mode assisted by an oscillation detection algorithm. Adaptive control strategies enable seamless transition between fast voltage regulation and effective oscillation damping, ensuring compliance with both voltage control and grid damping requirements. To test and verify the POD function, field tests and computational simulations are done, using a procedure and accurate electrical models. Real implementation in large-scale followed by proper commissioning procedure was conducted. Field results show the POD-Q open-loop performance fulfilling the expected phase shift and the respective grid code requirement. The value and use of accurate simulation models is particularly significant when a POD-Q function is involved. The models validation process involved comparing the simulation results with the field measurements, assessing phase shifts and amplitudes. Results from the simulation models remain aligned with the field performance, demonstrating the capability of this function and models.”

The impedance-based stability analysis is emerging as a common method to evaluate the stability of networks containing large shares of inverter-based resources (IBR, incl. HVDC VSC/MMC) in the sub-/super-synchronous and harmonic frequency ranges. The analysis can be applied to evaluate the system stability in the frequency domain regarding the identification of unstable system configurations or remaining stability margins. The method requires the evaluation of frequency-dependent equivalent impedances of the power system. The two major approaches to determine the frequency-dependent equivalent power system impedances are the “frequency scan” in the time-domain (EMT simulation) and the “frequency sweep” in the frequency domain by means of frequency-dependent impedance characteristics. Differences between both approaches as well as the respective advantages and challenges have been discussed in a previous publication. The major advantages of the frequency sweep are reduced computational cost and the use of look-up tables for the IBR equivalent impedances, i.e. no need to exchange highly detailed EMT models.

As part of a prior publication, the frequency sweep method has been implemented to carry out single-connection assessment, for example grid connection assessment of a single IBR or of an aggregated model of a power plant consisting of multiple IBRs. This is done by evaluating the Nyquist criterion of a SISO system (single input single output), where the stability of the extended power system is assessed. This also includes the consideration of the coupling over frequency effect, where voltage perturbations at one frequency can cause currents at a shifted frequency via transfer impedances of IBRs. The effect is inherently considered in the frequency scan, but needs to be explicitly modelled for the frequency sweep.

This paper expands on the previous work and presents the application of the frequency sweep for multi-connection assessment with consideration of operating point dependencies and the coupling over frequency effect. This is especially of interest for frequencies below the 2nd harmonic order. The methodology for consideration of the coupling over frequency effect in the frequency sweep for multi-connection assessment is explained and derived theoretically.

While the single-connection assessment requires that both the newly connected plant as well as the network including all other plants are stable on their own, the multi-connection assessment evaluates the stability of a MIMO system (multiple input multiple output), which can split the network into a passive or known stable part and the group of newly added IBRs or plants. This is especially relevant for larger power systems for which the stability of the network itself is often unknown, since not every future operating point and switching configuration is tested and known to be stable. Furthermore, long-time network planning uses drastically modified networks, for which the overall stability is unknown. Setting up detailed EMT models for future expansions with all their uncertainties would be a major challenge. Analysis based on a frequency-domain model can simplify the effort required to create suitable power system models, including the consideration of contingency cases.

An example of a power system is provided to showcase the application of the frequency sweep for the multi-connection assessment under consideration of the coupling over frequency effect and operating point dependency.

As part of the EU-funded PEACE^[1] project, an innovative, efficient alkaline electrolyser is being developed that will significantly reduce the costs of hydrogen production thanks to a two-stage pressurisation concept. A key aspect is operation at up to 90 bar, which both increases the efficiency of the overall system and simplifies downstream process steps by eliminating compressor stages. Higher pressure reduces the change in gas volume during load fluctuations, which has a positive effect on dynamic operation, but also increases the solubility of the gases, making gas purity more critical.^[2]

To analyse this dynamic operation, the TEMPEST^[3] simulation framework was parameterised and expanded for high-pressure operation. TEMPEST allows the investigation of the steady-state and transient behaviour of process engineering systems with electrochemical reactors. The focus here is on developing operating strategies and analysing scaling approaches. Critical parameter distributions within the cells (temperature, current density, flow rate, composition) are resolved in detail.

This work describes the application of TEMPEST to the high-pressure alkaline electrolyser of the PEACE project. Various operating strategies are evaluated with regard to their suitability for ensuring high gas purity and uniform temperature distribution. The simulation studies are carried out in close synergy with experimental investigations, which provide both parameterisation and validation data. This results in simulation-based findings that enable targeted experiments and also analyse operating conditions that go beyond the experimentally accessible range.

[1] https://www.h2peace.eu/

[2] A. Roy et al., Comparison of electrical energy efficiency of atmospheric and high-pressure electrolysers, doi.org/10.1016/j.ijhydene.2006.01.018

[3] M.Tomberg et al., Transient Modelling of Solid Oxide Cell Modules and 50 kW Experimental Validation. Stuttgart (2019), ECS Trans. 91

Energy usage optimization algorithms for cost-effective and resource-saving production are already widespread in industry. However, many optimization models disregard the uncertainty in the prediction of electricity and heat demand or in the forecast of solar energy feed-in. This paper describes an experimental optimization process for a cross-sectorial energy system with the task of taking uncertainties into account during the optimization in order to plan energy consumption from the grid. To accomplish this objective a new approach for scenario generation based on historical measurements and predictions is presented and explained in detail. At first, the optimization problem for the energy system is implemented as a deterministic problem which neglects uncertainties. Secondly, this problem is extended to a stochastic optimization problem using the aforementioned scenario generation and is solved in the extensive form. Both types of optimization problems are solved over a period of five months in a rolling process. The comparison of the experiments show that stochastic optimization is a good alternative to optimize with respect to uncertainties but comes with higher costs and longer computation time.

This paper proposes an improved chopper buffer circuit designed for current source converter (CSC)-based doubly fed induction generators (DFIG), aiming to significantly enhance their low-voltage ride-through (LVRT) capability. The proposed circuit consists of a resistor-capacitor branch with controllable switches, connected in parallel to the DC link, which effectively suppresses overcurrent in the DC inductor and optimizes DC current dynamics. Simulation tests under varying DC inductance values are conducted to evaluate the LVRT performance of the CSC-based DFIG, verifying the effectiveness and feasibility of the proposed chopper buffer solution.

The transition toward electric mobility is reshaping transport and energy systems, raising new challenges for the deployment and management of charging infrastructure. Existing research has largely centred on urban contexts, leaving rural and tourism-driven regions comparatively underexplored. This paper provides an empirical assessment of Scotland’s public EV charging network, combining a national-scale analysis of session-level utilisation data with a focused case study of the Highland Council area, a region where low population density, geographic dispersion, and demand seasonality intersect. The results show that charging demand in this area is marked by strong temporal fluctuations, with peak usage closely tied to seasonality and tourism windows, while off-season utilisation remains low. These dynamics highlight the limitations of conventional planning approaches that rely primarily on average utilisation metrics. Instead, infrastructure provision in such regions must be informed by context-sensitive planning and targeted strategies, such as demand-responsive expansion, co-location with local energy systems, and alignment with broader decarbonisation goals, to exhaust infrastructure effectiveness without necessitating continuous capacity growth.

The transmission system operator (TSO) must guarantee network stability, today and considering future developments. For example, the TSO must ensure that it always has the necessary reserves to maintain frequency within acceptable ranges, as well as the assets capable of delivering these reserves with the correct dynamics. As wind and solar generation increases in the energy mix, renewable energy producers must increasingly contribute to system flexibility. In France, for example, some of them are currently required to have the capability of providing automatic frequency control (frequency containment reserve (FCR) and automatic frequency restoration reserve (aFRR)).

For providing FCR and/or aFRR, wind and photovoltaic farms will operate below their optimum operating point, P_available(t). If they participate in the delivery of a symmetrical frequency service, they will have to reduce their power output to provide FCR and/or aFRR around a base power P_base(t), where P_base(t) = P_available(t) – Scheduled_Reserve_FCR – Scheduled_Reserve_aFRR with Scheduled_Reserve_FCR and Scheduled_Reserve_aFRR the amounts of scheduled reserves. If the regulation is only downwards (as it is allowed for aFRR), P_base(t) can be equal to P_available(t). However, in both cases, symmetrical and unsymmetrical regulations, it is necessary to know the value of the optimum operating point, P_available(t), at each time in order to compute a reliable setpoint P_setpoint(t) that includes the participation of the renewable asset in frequency control P_FCR(t) and P_aFRR(t), as P_setpoint(t) = P_base(t) + P_FCR(t) + P_aFRR(t). Once the set point has been established, the power must then be released by the wind or photovoltaic farm with the correct dynamics.

The main issue here is that, when the wind or photovoltaic farm is operated below its optimum operating point, the value of P_available(t) cannot be measured and must be estimated. As with any estimate, there is a margin of error on the estimated value and this error will be reflected in the setpoint calculation P_setpoint(t). Inaccurate computation of the setpoint could result in insufficient delivery or availability of the reserve on the asset. As an example, if we consider a wind farm providing only symmetrical aFRR, the effective available reserve upwards Real_Reserve_aFRR will be equal to P_real(t) - P_base(t), where P_real(t) is the effective power that can be extracted at time t from the wind, but if P_real(t) << P_available(t) then Real_Reserve_aFRR << Scheduled_Reserve_aFRR, the amount of scheduled aFRR.

This paper aims to address this issue based on an internal statistical study of lab data. First, it assesses the impact on French reserves if no action is taken to address the estimation error in P_available(t). Then, it presents the solutions that RTE is considering to secure its reserves, taking advantage of renewable energies' arrival as new key players in power system stability.

The International Energy Agency's (IEA) projects that global renewable electricity generation will reach nearly 90% by 2030, reaching over 17,000 TWh and that this decade will see renewables achieve several key milestones: overtaking coal in 2025, surpassing nuclear (both wind and solar) in 2026, and solar PV becoming the dominant renewable source by 2029, followed by wind in 2030 as both eclipse hydropower. In order to keep the lights on, integration of renewables into system operation and power market trading experience new challenges, similar to those at the outset of the journey into renewable power generation. One tool for dealing with the weather-driven energy sources is forecasting.

In order to meet the challenges in the continuously changing landscape of renewable generation, several IEA task force groups have been built. Two dedicated tasks deal with forecasting:

PVPS Task 16 aims to facilitate the integration of photovoltaic (PV) systems into energy grids by reducing costs and uncertainties related to solar resource assessment and forecasting.

Task 51, under the IEA Implementing Agreement for Co-operation in the Research, Development, and Deployment of Wind Energy Systems (IEA Wind) focuses on improving the value of renewable energy forecasts.

The challenges are large, but with a common understanding of forecasting and evaluation principles, exchange and definition of the requirements on data and instrumentation and rules and procedures on quality control, the electric grid can be efficiently and safely operated. An international community can provide objective information and bring together stakeholders and developers to shape standards that enhance the comparability and enable accessibility of methods on a global level.

PVPS Task 16 and IEA Wind Task 51 have established collaborative work related to the further development of forecasting tools, value of forecasting on different horizons from minute-scale to seasonal forecasting, as well as instrumentation and quality control for forecasting purposes. The collaboration is necessary in a world, where power generation from Wind and PV is becoming the two driving factors in the system operation of most countries.

The presentation of will provide an overview of the activities and accomplishments in the first phase of Task 51 (2022-2025) and a summary of the plans and new topics to be addressed in the second phase of the Task (2026-2029).

This paper presents a multi-layered framework for modelling large-scale electrical loads in support of grid compliance studies. The framework provides consistent representations in both electromagnetic transient (EMT) and electromechanical (RMS) simulation domains, ensuring robust validation against Transmission System Operator (TSO) requirements. It is organized into three generic layers: a model logic layer that integrates control, protection, and physical dynamics; a communication layer that enables input/output handling and software interfacing; and a simulation tool specific layer that ensures accurate representation within different environments. The framework is implemented in MATLAB/Simulink®, compiled into encrypted Dynamic-Link Library (DLL) files, and deployed in PSCAD® and DIgSILENT PowerFactory®, guaranteeing cross-platform consistency. The physical

dynamics were captured using a data-driven system identification approach, where transfer functions were inferred directly from operational datasets rather than derived from first-principles modelling. Validation included both benchmarking against operational data and application of the open-source Model Test Bench (MTB) tool developed by Energinet, demonstrating robust and grid-compliant performance under both normal and abnormal conditions. The methodology is generic and can be applied across different demand-side technologies, supporting the integration of flexible demand into future power systems.

Hybrid photovoltaic–battery energy storage system (PV-BESS) power plants are emerging as strategic grid-friendly assets, combining variable renewable generation with short-term flexibility. This case study focuses on a full year of operation of two French hybrid sites—8 MWp PV plus 3.8 MW 1h BESS and 18 MWp plus 7.5 MW 1h BESS—each subject to grid-connection contracts limiting active-power export to 50% of total capacity.

Goal: Maximise photovoltaic production revenues while complying with strict export caps and network operators grid codes and extending battery lifetime.

Results: Over a 7-month and a 12-month period, battery economic performance ranged from 89% to 95% of equivalent perfect forecast scenarios. A remarkable result is that the hybrid configuration retains over 95% of the gross margin generated by a configuration of standalones PV and BESS, while the injection max power capacity contracted with the electricity network operator in the hybrid configuration is no more than 50% of the sum of the injection max power capacity in equivalent standalone configuration.

Methods: The optimization is based on hierarchical, multi-scale At Level 2, the Unit Commitment process is structured as a two-level decision-making framework. The first level relies on a day-ahead dispatch strategy based on dynamic programming. The second level involves a mixed-integer linear programming (MILP) optimisation, which co-optimises energy arbitrage, ancillary service provision, and degradation cost minimisation, under both price and meteorological uncertainty. These two-steps decision processes are fed by a probabilistic set of weather scenarios. The second step of the Level 2 optimization process can be repeated during intraday (Level 1). Level 0 governs real-time set point tracking through decentralised control logic implemented on edge-level hardware, ensuring compliance with unit commitment schedule, power-quality and fault-resilience requirements.

The hybrid PV-BESS system model combines three complementary steps. A machine-learning model captures photovoltaic performance as a function of solar irradiance, weather conditions and geometrical positioning. Then, the physics-based dynamic programming and MILP optimisation account for the site's intrinsic operational constraints. Battery degradation is evaluated through a laboratory-calibrated electrochemical ageing model. To address the sensitivity of dispatch decisions to forecast uncertainty, the framework uses a dynamically updated distribution of solar forecasts rather than single deterministic inputs.

Relevance of the subject: This study presents a field-validated, multi-objective optimisation framework for PV-battery systems under distribution grid constraints, integrating economic, technical, and environmental objectives. The architecture accounts for climatic variability, supports co-optimisation, uncertainty management, degradation-aware control, and aligns with evolving network operators’ grid codes. Its design ensures replicability and scalability across constrained distribution networks.

In conclusion, this study demonstrates the strategic role of hybrid systems in mitigating variable renewable generation (VRE) and in providing ancillary services, reinforcing their role as a novel asset category in the evolution of power system architectures.

The electrification of heavy-duty vehicles requires megawatt-scale charging infrastructure, but distribution grid constraints and high investment costs pose significant challenges. This work presents a decision-support framework for evaluating and optimizing conditional connection agreements (CCAs) between Distribution System Operators (DSOs) and Charging Point Operators (CPOs). The methodology employs a bi-level, multi-objective optimization approach using genetic algorithm to explore CCA configurations while nested optimizations evaluate grid reinforcement and storage investment strategies. Applied to a Norwegian scenario, results demonstrate how CCAs can provide mutual benefits for both parties, with storage investments becoming viable under decreasing grid reliability scenarios. By enabling dialogue and coordinated planning in the negotiation phase between the parties, the framework aims at facilitating policy and industry efforts toward efficient, scalable electrification of heavy-duty transport.

Germany’s ambitious goal of achieving carbon neutrality by 2045 necessitates a substantial expansion of renewable energy generation, with offshore wind playing a critical role alongside onshore resources. The country aims to scale up its offshore wind capacity to 30 GW by 2030 [1], nearly quadrupling the installed capacity reported by the end of 2024[2]. This rapid growth brings not only technical and logistical challenges related to infrastructure deployment but also significant implications for grid stability and integration.

To address these challenges, German transmission system operators (TSOs) Amprion and 50Hertz introduced the Offshore Grid Connection Rules (ONAR) in 2023. These guidelines aim to streamline the connection of offshore wind farms to the extra high-voltage grid and are closely linked to the national Technical Connection Rules (TCR), namely VDE-AR-N 4130 for extra-high voltage systems and VDE-AR-N 4131 for HVDC-connected generation units.

Unlike the well-established onshore grid connection process, ONAR represents a relatively new framework that, in several areas, remains subject to interpretation. This presentation seeks to clarify the offshore grid connection procedure as outlined in ONAR, highlighting key process elements and sharing practical insights from recent project implementations. Special attention is given to the requirements for simulation models and model validations, including the conformity studies and documentation necessary for obtaining Interim Operational Notification (ION) and Final Operational Notification (FON) from the respective TSOs.

The presentation will conclude with a set of practical recommendations aimed at enhancing regulatory compliance and supporting grid stability, based on lessons learned from ongoing offshore wind integration projects in Germany.

[1] https://www.bundesregierung.de/breg-de/service/archiv/windenergie-auf-see-gesetz-2022968

[2] https://www.offshore-stiftung.de/en/status-quo-offshore-windenergy.php

The integration of electrolysers with renewable energies to provide green hydrogen poses challenges in converter-dominated networks faced with weak grid connection. This paper presents a case study about a grid-connected green hydrogen plant that is part of the ongoing work of the Horizon Europe AGISTIN project. The AGISTIN project investigates the role of energy storages to integrate large industrial loads with renewable electricity. In this work, a photovoltaic plant provides the power to the electrolyser, where both plants operate in grid-following mode. The electrical-equivalent circuit model of the alkaline

electrolyser stack is derived from a measurement campaign. An energy storage system operating in grid-forming mode is added. The converter control is based on literature. Time-domain simulations were performed on a real-time digital simulator using PLECS to investigate the integration of the electrolyser and the photovoltaic plant into a grid with various grid strengths. The results indicate that the grid-forming energy storage system allows operation in weak grids, as well as in island mode operation.

The forecasting for renewable energy community has been active since the first wind energy projects were built in Denmark in the 1990s. More than 30 years later, there are still no standards for the inputs into forecasting models and their output, or the evaluation of the performance of renewables generation forecasts. At the end of 2022, the IEA Wind Task 51 "Forecasting for the Weather-driven Energy System" launched its first Recommended Practice on the Implementation of Renewable Energy Forecasting Solutions, an industry guideline on forecast solution selection, forecast evaluation and collection and quality control of forecast input and verification data and instrumentation requirements.

Since then, the IEC Subcommittee 8A on Grid Integration of Renewables Workgroup 2 Renewable Energy Forecasting, has suggested to establish a standard for the evaluation of renewable energy power forecasting, including data preparation, statistics of indicators, evaluation of results and reporting. The standard shall provide a common understanding of the handling and quality of input data to forecasting of renewable energy as well as how data needs to be prepared and used in evaluation of renewable energy generation forecasts. It aims to close a gap in the understanding of forecasting processes on an international level that enables fair competition on forecasting methods and solutions and access to international markets. Both renewable energy power forecasting service providers and users will benefit from a common understanding of methods of evaluating forecasting for specific tasks and areas and enable transparent comparability of solutions.

The two work groups have joined forces on the development of the standard and will present the main features of the first working draft of the standard and discuss with stakeholders, whether the chosen approaches support forecasting service providers, users and research institutions on selecting, verifying and improving existing renewable energy forecasting techniques and its input data quality control.

The presentation will provide an overview to the current state of the draft, it's challenges and unresolved topics. The objective will be to promote a discussion with the stakeholders in the audience of the key issues and alternative approaches to address these issues.

When modelling energy system components for use in energy management systems, single-value coefficients or linearised characteristic curves are often assumed for the operating range. Frequently this approach proves to be too imprecise in predicting the system status. However, when determining operating point-dependent efficiencies, there are often gaps in the available information which can only be filled with an investment of time and effort. To address this, a parameter identification approach to determining the operating point-dependent efficiencies of energy converter systems was implemented and evaluated. Data from a vanadium redox flow battery out of the “Smart Region Pellworm” research project was used as the research object. A genetic algorithm was used to parameterise a simplified electrochemical surrogate model. With the help of the parameterised surrogate model, efficiencies and power limits were sampled over the entire operating range to create an easily transferable battery model for the prediction of state of charge responses to known unit commitment plans. A model with a fixed efficiency for charging and discharging and a model whose efficiency map is based on an experiment protocol were used as benchmarks for the calculated efficiency map. The approach was evaluated in terms of transferability and model error.

Scope

The widespread utilization of distributed generation highlights the appeal and feasibility of microgrids (MG). Decentralizing the electrical grid into smaller, self-sufficient segments enhances system resilience and operational continuity during disruptions, particularly under extreme conditions such as natural disasters or armed conflicts. Through the implementation of microgrid architectures that facilitate localized generation and consumption, critical power supply can be sustained even when the grid infrastructure is compromised. These MGs with high share of inverter-based generation rely heavily on grid-forming (GFM) inverters to provide voltage and frequency reference for the conventional grid-following (GFL) inverters.

To enable islanded operation, MG necessitates the capability of autonomous resynchronization to the main grid. GFMs are ideal assets for this, as they directly control the voltage and frequency of the local grid.

Methods

In our work we seek to investigate the capabilities of GFM inverters to successfully resynchronize the local grid considering (1) line impedances between inverters and the point of common coupling of the MG, (2) the share of GFM power relative to the overall power capacity of the MG and (3) the operating points of each individual GFM inverters. Through simulations, we also evaluate and enhance the tuning of the dedicated control scheme that facilitates reliable resynchronization among multiple GFMs.

The topic was investigated both in Matlab Simulink simulation and in laboratory environment through Power Hardware-in-the-loop (PHIL) simulations. The laboratory setup contained multiple physical assets as well as an extensive low voltage distribution system with multiple consumers and prosumers implemented on a real-time simulator.

Main results

We present a thorough investigation of multiple GFM inverters’ ability to cooperate in reconnecting a local grid based on multiple aspects. Key factors include the positioning of the GFM in relation to local consumers and prosumers, as well as the microgrid’s point of interconnection with the main grid, along with the nominal power and operational setpoints of the GFMs relative to local energy demand and generation capacity.

As part of its sustainability strategy, BMW is pursuing bidirectional charging as a key technology to integrate battery electric vehicles (BEVs) into the energy system. In the joint research project Bidirectional Charging Management (BDL), BMW and its partners from the energy and research sectors developed and tested vehicle-based flexibility use cases both behind and in front of the utility meter.

The project confirmed the technical feasibility and systemic benefits of bidirectional charging through simulations, laboratory setups, and a field test with more than 50 BMW electric vehicles. Results demonstrated household electricity cost savings of around 7.5% through PV self-consumption optimization (V2H), higher savings for households with energy-intensive assets such as heat pumps, and potential reductions of peak loads in business environments (V2B). Participation in intraday markets (V2G) yielded up to €90 per month per vehicle. Modeling further showed that large-scale adoption of aggregated BEVs can reduce the need for stationary storage and lower total cost of ownership.

Building on these results, BMW is now engaged in the follow-up project BDL Next, which evaluates mass-market readiness with the BMW Neue Klasse iX3 in real customer scenarios. The project focuses on seamless integration of vehicles into household energy systems, tariff optimization, and participation in grid services within a standardized and customer-friendly framework.

Summary

The trading of electricity from renewable energies poses a challenge for market participants, as the trading decision must be made before the delivery with uncertainty about the future generation of the renewable energy plants. Battery storage systems can reduce these uncertainties by being used to compensate for forecast errors of renewable energy plants. However, battery storage systems can also be used for arbitrage trading. In this work, reinforcement learning (RL) is used to determine the optimal trading strategy for battery storage systems on the short-term energy markets. Artificial neural networks are used, which are trained with the PGPE learning algorithm. The results show that the RL approach generates 7.3% higher profits compared to equation-based optimisation by reducing costs by 90 % through cyclic ageing.

Introduction

The trading of electricity from renewable energies poses a challenge for market participants, as the trading decision must be made before the delivery with uncertainty about the future generation of the renewable energy plants. Battery storage systems can reduce these uncertainties by being used to compensate for forecast errors of renewable energy plants. However, battery storage systems can also be used for arbitrage trading. In this work, reinforcement learning (RL) is used to determine the optimal trading strategy for battery storage systems on the short-term energy markets. Artificial neural networks are used, which are trained with the PGPE learning algorithm. The results show that the RL approach generates 7.3% higher profits compared to equation-based optimisation by reducing costs by 90 % through cyclic ageing.

Methodology

RL is used to determine the optimal trading strategy for a system pool consisting of renewable energy systems and flexible battery storage systems on the short-term markets. On the one hand, the battery storage systems are used for arbitrage trading. On the other hand, they are also activated for short-term balancing by providing or absorbing energy at short notice to mitigate forecast errors.

The latest status and forecast data of the plants are used to determine the optimum utilisation of the power plants in order to create the bids on the day-ahead and intraday markets. As shown in Figure 1, policy gradients with parameter-based exploration (PGPE) and artificial neural networks are used as learning algorithms for function approximation. The cyclic ageing is determined by the Rainflow algorithm. The results are compared with an equation-based optimisation approach (EB).

Results

In this work, it was demonstrated that RL optimisation of storage utilisation achieves higher profits compared to established methods by extending the lifetime of the battery storage system. As shown in Figure 2, RL optimisation results in higher imbalance settlement costs than EB optimisation due to greater deviations between the amount of energy offered and physical delivery. At the same time, the cycling ageing costs of RL-optimised storage use are only 11% of the ageing costs of storage use with EB optimisation. Overall, this means that RL optimistion achieves 7.31% higher profits than EB optimisation.

This study presents a comprehensive Geographic Information System (GIS)-enabled analysis aimed at evaluating land eligibility for renewable ammonia production in Kenya. The general scope of the research focuses on assessing the suitability of various land areas by combining renewable energy potential, environmental factors, and existing infrastructure.

Utilizing a combination of remote sensing data, land use maps, and environmental datasets, we conducted a multi-step GIS analysis. The methodology involved spatial data processing, suitability modeling, and overlay analysis to identify optimal regions for ammonia production. A key component of the GIS analysis was the use of the Analytic Hierarchy Process (AHP) to prioritize various criteria relevant to ammonia production with the help of experts and local stakeholders. This method allowed for a structured assessment of factors such as access to water sources, solar energy potential, soil quality, and transportation infrastructure. By combining these criteria with the land eligibility analysis, we were able to identify suitable locations and compare them on an easy-to-understand scale.

The relevance of this research lies in its potential to significantly enhance agricultural productivity in Kenya by offering sustainable, locally produced fertilizers. This approach addresses the growing demand for fertilizers and aims to reduce the country's dependence on imported chemical fertilizers, which can be both costly and environmentally detrimental.

The major conclusions drawn from this study underscore the importance of a thorough GIS-based land suitability analysis in informing decision-makers for renewable ammonia production. By highlighting optimal locations, this research contributes valuable insights to stakeholders, including policymakers, agricultural producers, and renewable energy developers.

This research presents a flexibility simulation tool developed under the EU-funded project AHEAD to address the challenge of managing EV charging in parking facilities with limited grid capacity. Using field data from an industrial campus in Lisbon, Portugal, the study demonstrates practical solutions for minimizing peak loads in congested secondary substations through load shifting strategies. The tool optimizes charging schedules for over 60 charging points connected to a single 630 kVA substation. It employs Linear Programming (LP) techniques to implement load shifting strategies, considering individual vehicle requirements, arrival and departure times, and grid constraints. Monte Carlo Simulation is used to evaluate future scenarios with varying EV adoption rates and usage patterns. Three primary scenarios were tested: standalone configuration, integration with photovoltaic generation, and integration with bidirectional chargers. Preliminary results show significant potential for peak load reduction, achieving 20-30% reductions compared to uncontrolled charging. The bidirectional charging scenario shows a reduced impact for large homogenous EV fleet clusters. The tool demonstrates that controlled charging management can substantially improve infrastructure utilization efficiency, offering valuable insights for facility managers and grid operators to enhance existing infrastructure capacity without costly investments.

As converter based renewable energy systems continue to penetrate the electric power grid, regulatory standards for grid interconnection continue to evolve. One of the most challenging requirements for generative systems is the injection of valuable reactive currents during Low-Voltage Ride-Through (LVRT) events, especially during asymmetric LVRT situations. As state-of-the-art, Phase Looked Loops (PLLs) are used to determine the corresponding amplitudes and phases of positive- and negative-sequence voltages, however, they show an inherent limited dynamic response during LVRT events. Therefore, this paper investigates an estimation algorithm for the positive- and negative-sequence systems that is based on the online elliptical approximation of the voltage space vector trajectory. The algorithm shows fast dynamic performance with regard to grid faults. The real-time capability of the algorithm is shown by implementation on a novel Field Programmable Gate Array (FPGA) based platform. The dynamic performance of the proposed algorithm is shown by direct comparison to common PLL methods.

With the increasing integration of wind turbines, series capacitor compensation is widely used to improve transmission efficiency but raises the risk of sub-synchronous oscillations (SSO), especially in doubly fed induction generator (DFIG) systems. The slip-dependent rotor resistance can introduce a negative resistance effect on the stator side, potentially destabilizing the system. This study investigates the mechanisms of sub-synchronous resonance (SSR) in DFIG-based systems using mathematical modelling and impedance analysis. To enhance stability, a novel sub-synchronous stator flux injection method is proposed. This approach effectively reduces the equivalent mutual inductance, mitigating the stator-side influence of rotor-induced negative resistance and significantly improving damping performance. Impedance scanning and simulation results validate the theoretical findings, demonstrating that the proposed method provides a robust means to suppress SSR in series-compensated DFIG systems.

As Germany transitions toward a renewable-dominated energy system, additional system inertia is needed to ensure frequency stability and grid resilience. A market to procure Inertia Services is currently being started.

The contribution will give an overview on the status of the inertia market – with regulatory, commercial and technical aspects being summarized. The contribution outlines the key performance metrics and how they interact with Battery Energy Storage Systems (BESS) plant design and revenue streams. A comparison of the long-term (10 year) market vs. the 1-year-ahead market in UK is provided.

A key aspect is the deployment of BESS optimized for inertia emulation. We highlight an innovative approach based on an inverter hardware platform that is optimized for inertia provision – being capable of delivering up to 18 GWs of synthetic inertia per 1 GW of rated power, by using the latest grid-forming controls and short-term peak power capabilities. This solution allows flexible service stacking in multi-use applications such as energy arbitrage, frequency control, and system restoration.

The paper also presents international best practices from Scotland, including the world’s first transmission-connected BESS providing inertia and short-circuit support.

We discuss the status of the inertia market, including some insight into the ongoing certification process, and overall situation of the deployment of the new market and technology in Germany.

As power systems transition toward high shares of renewable energy, synchronous generators are being phased out. In their absence services including inertia, system strength and instantaneous fault currents must be provided by inverter-based resources. Inter-area and local oscillations may change in their nature at lower shares of conventional generation – thus inverter-based resources need to provide adequate damping power as well.

This contribution outlines how the key stability services can be provided from Battery Energy Storage Systems (BESS) and photovoltaic (PV) systems. BESS can be optimized to provide high amounts of inertia – to buffer the power imbalances of extreme events like system splits. Fast transient voltage control for both PV and BESS increases system strength and ensures a stiff local voltage. And PV and BESS further contribute to power oscillation damping, thereby mitigating both inter-area and local-area oscillations – even when the oscillatory modes related to synchronous machines change over time.

We will present how BESS can be the main anchors for stable system, and how PV systems contribute to stability. The focus is on the available technology, which is already in use.

One key scenario is the large active power disturbance as a result from e.g. a system split. This directly benefits from the extremely fast frequency support from inverter-based resources. But only the instantaneous reaction from inertia in BESS ensures the proper functioning of these frequency support functions (i.e. limited frequency sensitive mode), and even then load-frequency disconnection schemes may be necessary to stabilize the (partial) system. The combination of highly available and robust inertia along with load shedding plans and fast LFSM ensures safe and reliable power systems.

This paper presents the view from OEM perspective on how BESS, PV, and wind generation can collectively provide all the necessary ingredients for a stable and secure power system that is mainly based on renewable generation.

The challenge of decarbonising the energy system increasingly depends on the electrification and system-compatible integration of customer infrastructures, neighbourhoods, and electric vehicle (EV) charging clusters. Effective management of this transition requires the coordination of energy supply with the electricity grid and energy markets. This includes the targeted utilisation of local energy resources, such as photovoltaic (PV) systems and combined heat and power (CHP) plants. Aligning consumption with generation and grid availability represents a short-term strategy to avoid grid congestion—particularly in low-voltage networks—and is more cost-effective than extensive grid reinforcement. Additionally, such alignment aims to enhance overall system efficiency by maximising the use of renewable energy sources and minimising the reliance on temporary storage solutions.

The CACTUS project focuses on optimising grid utilisation and leveraging local energy flexibility within the distribution grid, with a particular focus on commercial and business parks. A key component of this approach is the implementation of dynamic grid fees. This adaptive pricing mechanisms is designed to provide financial incentives for decentralised, automated energy systems, such as EV charging clusters and aggregators. These systems can react to the price signals on different time-scales, thereby lowering electricity procurement costs and enabling increased connection capacities without necessitating costly grid expansion.

Additionally, a tool with the “Connect–Assist–Control” methodology is being developed in this project. It will support grid operators through the following elements:

• Connect: Enabling communication with customer systems via standardised interfaces
• Assist: Visualising grid congestions and proposing mitigation measures
• Control: Modulating price signals to proactively manage grid capacity and prevent overloads

By dynamically adjusting price signals, the system can accommodate fluctuations in generation and consumption, thereby helping to maintain voltage stability. This reduces the need for emergency interventions such as forced disconnections or load shedding, which are typically employed only as a last resort to avert grid failure. The conference presentation will outline the objectives and current progress of the CACTUS project, offering insights into addressing regulatory and technical interface challenges. Particular emphasis will be placed on the design of a user-friendly and efficient incentive system that incorporates both market signals and grid constraints to enable intelligent grid management. Furthermore, the integration of future user groups and the adaptability of dynamic grid fees will be discussed as critical factors for scalable and sustainable implementation.

The stability of a system influenced by power electronics depends to a large extent on the behaviour of the individual generation units, which is mainly influenced in the respective national grid codes. This requires a comprehensive and robust analysis of possible faults and occurring phenomena as well as the derivation and determination of the necessary behaviour of the plants. Especially regarding the behaviour in the first periods after fault occurrence and fault clearance, there are still open aspects in current grid codes. The basis of the investigations in this paper is an extensive research of real-world events, which are categorized in terms of their manifestations and severity. The focus is on events that have led to the disconnection of generation units. Relevant event sequences such as voltage profiles, phase angle jumps, and frequency gradients are subsequently implemented in the simulations. A toolchain is presented for the dynamic adaptation of derived networks and the analysis of identified faults, enabling large-scale electromagnetic transient (EMT) simulations to be conducted within modern power system analysis tools. Local and regional connection conditions are incorporated in the simulation framework. Subsequently, the transient behaviour of generating units in high-voltage power grids is investigated. The behaviour of a detailed modelling and an aggregated park model is compared and recommendations regarding necessary modelling depth is derived considering modelling complexity. The system behaviour and the influence of the fault cases is then combined with different shares of grid-forming (GFM) generating units to determine to what extent they can stabilize the system behaviour in the event of a fault and which penetrations are necessary.

Current energy system planning tools inadequately capture the impact of extreme weather events, particularly for systems with high renewable share. Energy system modelers increasingly recognize the need to systematically explore extreme events, with some efforts evaluating potential disruptions from cold spells and long-duration outages. Some studies have identified periods of wind and solar droughts, and scenarios from worst-case to multi-year challenges. However, identifying extreme events is highly dependent on the configuration of the energy system in use. Inconsistent testing methodologies may underestimate system vulnerabilities, highlighting the need for standardised stress testing approaches. Additionally, binary results (pass/fail) during extreme events lack comparability across studies and insight into how to improve the system design.

This study introduces a standardised method for stress testing energy system models under extreme weather conditions using the concept of a “survival surface”. Rather than simply determining whether a system can fail, our approach quantifies the margin by which it fails and identifies investments to remedy unserved demand. The survival surface identifies all viable combinations of three key components: (1) external transmission capacity, (2) storage capacity, and (3) back-up power generations. This surface contains configurations where supply meet demands with minimised investment cost. By plotting a given energy system as a point relative to its survival surface, we can quantify the system adequacy with precision. A system with components plotted on the same side as the origin relative to its survival surface is inadequate during the extreme event, and the optimal investment pathway is the perpendicular line to the nearest point on the survival surface. Additionally, comparing survival surfaces across different system designs can show which system is particularly vulnerable to that extreme event.

We integrate the method as a tool in the Calliope modeling framework to facilitate the use of this standardised method for a variety of energy system designs. The process takes a system design and weather time series (wind speed, radiation, temperature) as input and produces a three-dimensional survival surface as output. We showcase this tool with an extreme event in December 2007, a particularly low-wind cold snap, first for Germany, then in interconnected Central Europe, with different renewable scenarios for present-day, 2030, and 2050.

Our method provides a clear framework to evaluate system adequacy in withstanding extreme weather events, quantify the safety margin in three key components, and identify the optimal investment pathway. The integrated tool in the Calliope framework facilitates applications with a wide range of weather data and energy models, providing essential insights for planners and policymakers.

The rising share of flexibilities combined with the recent development of machine learning techniques has the potential to create a sustainable and efficient low-voltage grid infrastructure. The new operational challenges, as the increasing uncertainty of the production of renewable energy sources, have to be met by effective measures. To prevent or mitigate disturbances such as overloading of the operating equipment or excessive voltage deviations, a predictive operation based on an autoregressive model using Graph Neural Networks is presented in this paper. The proposed model enables an optimized grid operation over a period of 1-5 hours by curtailment of generation and consumption at individual grid nodes as well as the adjustment of transformer tap changer positions.

A Graph Neural Network, which was trained with load and generation profiles for grid operations, serves as the basis of the model. It determines a grid operation for any possible combination of load and generation which can be obtained by current measurements or by forecasts for load and generation for each individual household in the grid. The load and generation forecast as well as the operating strategy determined by the graph neural network in the previous time step serve as input for the autoregressive model. With this information, the subsequent grid state can be calculated and an adjusted graph created. This graph is loaded into the Graph Neural Network, which determines the optimal operating strategy. The strategy is passed on to the next time step through the autoregressive approach. Thus, it determines an operating strategy over a series of consecutive time steps.

The autoregressive approach enables predictive grid operation over multiple time steps that influence each other sequentially. For example, it can be taken into account that the generation of photovoltaic systems is lower if a reduction was determined in the previous step. The model is tested on a pypsa model of a real existing grid with high shares of renewable generation and flexible loads. For the evaluation of the autoregressive graph neural network algorithm, a ground truth is generated for the relevant time period. This ground truth is determined by sequentially testing various operating configurations for each time step in a freely selectable order until a disturbance-free configuration is found. The optimal solutions obtained in this way serve as a reference. The results show a clear dependency of the algorithm on the training quality of the underlying Graph Neural Network. With a suitable selection of training and test data, further work aims to improve the Graph Neural Network, which will increase the quality of the autoregressive model. This straightforward and intuitive architecture can prevent faults in real time by regulating controllable generation and loads and prevent the overloading of lines and transformer stations in the grid at an early stage.

The forecasting for renewable energy community has been active since the first wind energy projects have begun on Denmark in the 1990'ies. More than 30 years later, there are still no standards on forecasting model input and output, or on evaluation of renewables generation forecasts. At the end of 2022, the IEA Wind Task 51 "Forecasting for the weather-driven energy system" has launched its first Recommended Practice on the Implementation of Renewable Energy Forecasting Solutions, an industry guideline on forecast solution selection, forecast evaluation and collection and quality control of forecast input and verification data and instrumentation requirements.

Since then, the IEC Subcommittee 8A on Grid Integration of Renewables Workgroup 2 Renewable Energy Forecasting, has suggested to establish a standard on evaluation of renewable energy power forecasting, including data preparation, statistics of indicators, evaluation of results and reporting.

The standard shall provide a common understanding of the handling and quality of input data to forecasting of renewable energy as well as how data needs to be prepared and used in evaluation of renewable energy generation forecasts. It aims to close a gap in the understanding of forecasting processes on an international level that enables fair competion on forecasting methods and solutions and access to international markets. Both renewable energy power forecasting service providers and users will benefit from a common understanding of methods of evaluating forecasting for specific tasks and areas and enable transparent comparability of solutions.

The two work groups have joined forces on the standard development and will present the main features of the first working draft of the standard and discuss with stakeholders, whether the chosen approaches support forecasting service providers, users and research institutions on selecting, verifying and improving existing renewable energy forecasting techniques and it's input data quality control.

An inspirational talk will be used as start-up into an interactive session, where the general acceptance, the challenges and the prospects for the benefits of such a standard will be the topic of questions to the audience and the panelists in the following Q&A part.

Moderator: C. Möhrlen (WEPROG, Denmark), Panelists: Jan Remund (Meteotest AG, Switzerland), Sylvain Cros (Ecole Polytechnique, France), Andrea Meyer (Bern University of Applied Sciences, CH | TU Delft, NL), Hannele Holttinen (Recognis, Finland), Nickie Menemenlis (Hydro Québec, Canada), Jonathan Dyson (Greenview Strategic Consulting, Australia), Debra Lews (ESIG, USA)

The International Energy Agency's (IEA) projects that global renewable electricity generation will reach nearly 90% by 2030, reaching over 17,000 TWh and that this decade will see renewables achieve several key milestones: overtaking coal in 2025, surpassing nuclear (both wind and solar) in 2026, and solar PV becoming the dominant renewable source by 2029, followed by wind in 2030 as both eclipse hydropower. In order to keep the lights on, integration of renewables into system operation and power market trading experience new challenges, similar to those at the outset of the journey into renewable power generation. One tool for dealing with the weather-driven energy sources are forecasting.

In order to meet the challenges in the continuously changing landscape of renewable generation, several IEA task force groups have been built. Two dedicated tasks deal with forecasting:

PVPS Task 16 aims to facilitate the integration of photovoltaic (PV) systems into energy grids by reducing costs and uncertainties related to solar resource assessment and forecasting.

Task 51, under the IEA Implementing Agreement for Co-operation in the Research, Development, and Deployment of Wind Energy Systems (IEA Wind) focuses on improving the value of renewable energy forecasts.

The challenges are large, but with a common understanding of forecasting and evaluation principles, exchange and definition of the requirements on data and instrumentation and rules and procedures on quality control, the electric grid can be efficiently and safely operated. An international community can provide objective information and bring together stakeholders and developers to shape standards that enhance the comparability and enable accessibility of methods on a global level.

PVPS Task 16 and IEA Wind Task 51 have established collaborative work related to the further development of forecasting tools, value of forecasting on different horizons from minute-scale to seasonal forecasting, as well as instrumentation and quality control for forecasting purposes. The collaboration is necessary in a world, where power generation from Wind and PV are the two driving factors in the system operation of most countries.

An inspirational talk will be used as start-up into an interactive session, where the challenges of renewable energy forecasting with a penetration level of 80% or more renewables in the grid are the focus point around the questions to the stakeholders in the audience and later on from the panellists.

As part of the transition to an energy system with 100% renewable generation, renewable energy power plants must increasingly take over responsibility for system stability. A key element in ensuring system stability is grid forming control of generation and storage units. In Germany, scenarios predict a significant expansion of renewable energy generation and storage systems in distribution networks. Integration of grid-forming systems into distribution networks raises several open questions, among them are power system oscillations and temporary island operation: Grid forming inverters may unintentionally lead to oscillation issues like those found in traditional transmission systems. A study reveals that as the level of virtual inertia in the distribution grid increases, these oscillations may become more pronounced which highlights the importance of implementing effective damping measures. Temporary island operation: In principle, grid-forming inverters enable the stable continued operation of critical sub-grids after a fault-related disconnection from the supply grid. Both disconnection and interception of the grid, as well as resynchronization and reconnection of the sub-grid with active generators and consumers are simulated in a series of laboratory tests and the basic suitability of this technology and the necessary requirements for this application are explained

The research presented in this paper is supported by the German Federal Ministry for Economic Affairs and Energy in the frame of the project “Verteilnetz2030plus” (FKZ 03EI4067). The authors are solely responsible for the content of this publication.

This work explores the implementation of coordinated control for a portfolio of electrolyzers.

The Power-to-X technologies are expected to become an important part of Offshore Energy Hubs (OEH), offering demand-side flexibility, optimizing wind energy production and providing power balancing services. The latter implies the implementation of a control strategy for a large-scale electrolysis plant, which can consist of a variety of electrolyzers with different flexibility capabilities. The identical control strategy implemented for electrolyzers with different parameters within one electrolysis plant can lead to non-optimal operation of electrolysis plant and can cause negative consequences, such as power oscillations between the two types of electrolyzers.

The dynamic models of 4 electrolyzers were implemented with different characteristics, including different ramp-rates, partial loading limitations, and hot-startup ramp rates. The electrolyzer portfolio was connected to a 4 GW offshore energy hub and equipped with AGC control to mitigate power imbalances and shutdown control for prolonged frequency disturbance. At first, the non-coordinated setup, meaning the identical control settings, was simulated with several positive and negative power imbalances, caused by tripping of HVDC line and the wind power plant, respectively. The simulation showed fluctuations related to two different problems: one is an identical AGC coefficient that causes hunting between electrolyzers, the other is the same shutdown time that can cause the reverse imbalance and, hence, provoke the startup procedure. Both problems were addressed by applying control settings in a coordinated manner, considering electrolyzers' ramp rate capabilities and partial load limitations. The coordinated electrolyzer portfolio showed improvement in response to power imbalance.

This work results and conclusions are based on the master's thesis work.

To address the low inertia grid inverters sources provide, the virtual synchronous machine (VSM) has been one of the main approaches to regulate the active power in continuous time domain. However, continuous time solutions do not take into consideration some of the dynamic behaviors of the system, such as measurement delays and small number of samples per period, given by the limitations of the hardware used to implement these controls. This is where careful discrete design is important, taking into consideration these hardware limits to obtain reliable results. This paper presents a discrete implementation of the VSM using the direct discrete modeling method, along with a comparison between the continuous, exact discrete and an approximation. The finding highlights that the continuous and the approximation show deteriorating results the sample time increases. Only direct discrete modeling can match the ideal continuous domain design.

Assuming current market rules remain unchanged, the increasing penetration of photovoltaic (PV) systems and battery storage systems is expected to lead to an increase in Deterministic Power Imbalances (DPI) and thus Deterministic Frequency Deviations (DFD). The original cause of DPI can be traced back to covering continuously changing loads with generation based on hourly market products. This will increasingly be overshadowed by the balancing of continuously changing PV feed-in using fast battery storage, also based on hourly or quarter-hourly market products. Due to the scale of the problem − DPIs of up to 6 GW within a quarter of an hour are projected for 2030 based on a PV ramp of 13 GW/quarter hour − an effective solution must be found and implemented in the coming years. None of the promising countermeasures discussed in this paper offers a simple solution that can be implemented by transmission system operators (TSOs) alone. To sufficiently reduce the impact of DPIs, the option “additional provision of balancing energy” appears unsuitable due to the limited temporal responsiveness of aFRR. The option “trading with 5-minute products” has the potential to significantly reduce DPIs. However, implementation reamains uncertain in the near future, especially within the European context. The option, “Requirements and incentives for ramping”, is generally considered to be a suitable countermeasure for significantly reducing the impact of DPIs. It is currently considered to be the option with the fewest obstacles in terms of implementation and is therefore discussed in greater detail as a potential solution.

Scope

In recent decades, the increasing integration of renewable-based generation has significantly altered the composition of electric power systems. Despite this shift, conventional synchronous generators remain vital for uninterrupted operation due to their reliability and controllability. As system dynamics evolve, new modelling approaches are necessary to accurately assess stability. This paper presents a small-signal model of a representative transmission network comprising transmission lines, transformers, inverter-based resources, and synchronous generators. The model is used to analyse the impact of synchronous machine parameters (e.g. excitation control settings) on system stability.

Methods

An impedance-based small-signal modelling approach in the positive sequence domain is applied. While only positive-sequence components are modelled, the effects of frequency coupling caused by non-idealities in the grid and by DC sources are taken into account. Analytical expressions are derived for the impedance of each network component and validated using frequency scans in Matlab Simulink simulations. These impedances are then used in conjunction with the Bode stability criterion to assess the interaction between synchronous machines, converter-based generation and the grid, highlighting potential resonance conditions under different operating scenarios.

Main Results

Stability analyses are carried out for different network switching states, considering various generator excitation control parameters. The demonstration showcases the use of the small-signal models introduced throughout the work, identifying whether improper tuning could cause undamped resonances, particularly in the low-frequency range where the control of the synchronous machines' excitation and the converter-based generators' slow control loops (e.g. DC voltage control, PLL) are the most defining factors.

Grid-forming (GFM) control strategies are gaining traction in Type-4 wind turbines to support grid stability in low-inertia systems. While the external GFM response is typically evaluated at the point of interconnection, the internal subsystems—such as the DC-link, machine-side inverter, and their associated control loops—are often overlooked, and their impact on the grid-forming behavior remains insufficiently understood. This work aims to reduce this knowledge gap by formulating a system identification framework that captures the influence of these internal dynamics on GFM performance.

The approach is based on analytically deriving signal relationships that enable frequency-domain identification of key GFM metrics—such as inertia-like response, damping behavior, and bandwidth limitations. These metrics are extracted from simulation data using small-signal perturbations applied to detailed wind turbine models.

Results show how internal subsystem interactions can alter the expected GFM behavior, highlighting their influence under weak grid conditions and their role in shaping frequency and voltage response characteristics. This methodology provides a structured way to assess and compare the GFM capabilities of wind turbines, offering practical insights for both manufacturers and system operators.

Electric vehicle charging networks face critical vulnerabilities during power outages, where localized infrastructure failures create demand surges that propagate beyond immediate failure zones. This study presents a spatial-temporal assessment framework for electric vehicle charging network quality of service under outage scenarios using real-world Berlin data. We implement a zone-based approach modeling aggregate electric vehicle behavior across 25 Berlin subdistricts, incorporating 61,768 electric vehicles and 1,411 charging stations. The methodology integrates fuzzy logic charging decision systems with Berlin-specific operator tariffs and Markov Decision Process trip generation. Our analysis reveals counterintuitive vulnerability patterns where single-district outages create 227\% waiting time increases and neighboring districts experience more severe impacts than directly affected areas. Multi-district outages demonstrate non-linear escalation effects, generating 330\% waiting time increases with system-wide stress patterns extending beyond 20 kilometers from outage epicenters. These findings provide actionable insights for infrastructure operators and policymakers, demonstrating that coordinated failures pose disproportionate threats to urban mobility systems.

The increasing penetration of inverter-based generation in distribution grids, coupled with the replacement of synchronous gen-

erators in transmission grids, has a profound impact on the stability of the electricity grid. To address this, grid-forming (GFM)

controls for inverters that emulate the behaviour of traditional synchronous generators are essential. However, experience is

lacking regarding their impact on the system stability including the prevention of mutual interferences of the control algorithms.

Thus, the control interaction between two inverters operated in parallel to each other are investigated in a Power Hardware-in-the-

Loop microgrid. By systematically varying the active power control parameters of one inverter, the the dynamic power sharing

and its effect on the voltage and frequency between the two GFM inverters in the event of a repetitive load step was investigated.

The experimental test results demonstrate that unequal settings of the GFM control parameters decreased the stability of the

overall system.

Small-signal analysis of wind parks (WPs) connected to power systems is performed using either impedance-based analysis or state-space analysis. Studies that model wind parks using state-space equations have led to significant progress in identifying the causes of oscillations and its participation factors. However, unlike traditional synchronous generation, standardized and accurate analytical models of the dynamic behavior of WPs are not available. Furthermore, due to industrial secrecy issues, this information is typically not provided by manufacturers, who provide a black box EMT model for studies. Thus, although analysis using state-space equations brings advantages in analyzing the phenomenon, it may not be feasible when complete models are not made available by manufacturers.

In this context, the impedance-based approach has gained prominence to analyze oscillations due to wind park interactions with the grid. This approach uses the impedance profile as a function of frequency, i.e., terminal characteristics, which are obtained by frequency scanning from the model provided by the manufacturer. With the impedance model of the WP and the grid, the Nyquist criterion can be applied to verify stability or stability margin. This approach is effective for stability analysis.

To address the system small-signal analysis based on the impedance, the system is separated into the system and the inverter-based resource (IBR). The power system subsystem is modeled by its Thevenin equivalent circuit consisting of an ideal voltage source in series with an output impedance, while the grid-connected inverter is modeled as a current source in parallel with an output impedance. This is the typical analyses performed to evaluate the impact on small-signal stability of WP on power systems.

However, in power systems such as the Brazilian one, it is common for multiple WPs to share a single connection point to the transmission network. These WPs can have different technologies (type III or IV) and each wind turbine can have different nominal capacity. Thus, it is not practical to directly consider one single WP using typical aggregation techniques. Therefore, rather than evaluating the impact of a single WP, the collective impact of the WPs connected to a specific point of the system should be assessed.

This paper presents the procedure to compute the equivalent impedance representing multiple WPs based on the impedance model of each WP. The procedure is applied to case based on a point of coupling of different WPs connected to Brazilian interconnected power system. The equivalent system is modeled in EMTP, the WPs are represented by generic-EMT model of wind parks, and the impedance scan is performed to obtain the impedance model of each WP. The use of the method allows identifying critical operating conditions for that group of WPs connected to that point of connection, due to weak grid conditions.

In view of different sub-synchronous instability events in real power systems dominated by inverter-based resources (IBRs), impedance-based modeling has gained prominence for small-signal stability assessment. In this context, the present work aims to assess the impact of PV-side components on a two-stage PV impedance model. A sensitivity analysis was conducted regarding the DC-DC converter controller, the PV-side filter, and the solar module array, comprising the primary parameters. Additionally, this analysis was repeated under different conditioning variables, including irradiance level, DC-link capacitor, and DC voltage controller, which can affect the sensitivity to primary parameters. These parameters were varied collectively to investigate interdependencies. The first analysis indicated negligible sensitivity of the impedance profiles to the primary parameters. However, the second analysis drew a different conclusion when comparing the full model and a simplified one that disregards the PV-side components. Depending on the values of the conditioning variables, the simplified model may lead to inaccuracies.

Hybrid power plants (HPPs) support decarbonization and enhance grid stability by integrating renewable generation with complementary energy storage technologies. This study introduces a hybrid power plant controller (HPPC) for storage-oriented active power dispatch between a high-power storage technology (HIPST) and a high-energy storage technology (HIEST). The HIEST setpoint is determined based on the HIPST state of charge, preserving HIPST energy reserves and reducing cycling stress on HIEST. The controller operates in two modes: constant setpoint tracking and an adaptive smoothing mode using exponential moving average (EMA), which improves responsiveness under variable wind conditions. Time-domain simulations using realistic wind generation profiles from DTU CorRES, calibrated to the Lem Kær wind farm configuration, ensure practical relevance. Results highlight the critical role of tuning droop parameters and EMA settings to balance smoothing quality with efficient storage utilization. The proposed HPPC provides a practical solution for hybrid power plants, optimizing the operational roles of HIPST and HIEST while maintaining stable power delivery under dynamic conditions.

Among renewable energy generation technologies, wind energy is considered one of the most promising and energy-efficient. Therefore, its proper study is essential. This paper analyzes the preliminary stability of a semi-submersible platform for a wind turbine. Peruvian sea conditions are quite favorable for implementation, considering the average maximum wave height of 1.61 m near the coast of Chancay. Where wind speeds are 9 m/s and energy densities are 700 W/m².

One of the most important stability aspects is determining the natural frequencies of the floating structure. To achieve this, experimental tests will be conducted using a reduced-scale 1/40 platform model with a 5 MW power output and free decay tests to obtain the damping characteristics of the floating system. This information will validate numerical simulations using computational fluid dynamics (CFD) to determine free decay in roll, heave, and surge conditions, and tests under wave conditions in regular sea conditions for the free and moored platforms.

Driven by clean energy goals, power systems are undergoing a transformative shift with the increasing integration of renewable energy resources. Traditional centralized power plants, which interface with the grid through synchronous machines, are progressively being replaced by inverter-based resources (IBRs). As this transition accelerates, power grids are evolving from machine-dominated to inverter-dominated systems, resulting in weakened transmission and distribution networks in certain regions.

Reduced system strength and inertia could challenge the stable operation of conventional grid following (GFL) inverters as they are primarily designed to operate in the presence of a strong grid. Unstable operation or large-scale disconnection of GFL IBRs following disturbances challenges the reliability of both transmission and distribution systems. Real-world incidents reported by system operators such as the Electric Reliability Council of Texas (ERCOT) and the Australian Energy Market Operator (AEMO) underscore these concerns.

Grid-forming (GFM) IBR has been proposed as one of the solutions to address weak grid challenges. In the near term, they are primarily considered in transmission systems with low fault current and rotational inertia, and in distribution inverter-based microgrids. Transmission-connected GFM IBRs have been shown as beneficial in addressing weak grid challenges. Some transmission system operators (e.g., Hawaiian Electric, FINGRID) have started requiring GFM capability from the transmission-connected IBRs. However, the potential need for and benefits of GFM inverters in distribution systems under grid-connected (blue-sky) operating conditions remain insufficiently explored.

Previous work by the authors [1] has demonstrated that GFM distributed energy resources (DERs) can enhance local stability by supporting nearby DER operations. Building on this foundation, this paper extends the analysis to a broader, system-wide perspective, focusing on scenarios where DERs contribute a substantial share of total generation capacity. Such high-penetration scenarios are already a reality in regions like South Australia, where distributed PV met over 90% of demand during certain periods in 2021 and 2022. Using electromagnetic transient (EMT) simulations in PSCAD/EMTDC, this study evaluates how high DER penetration affects system-wide oscillation damping and frequency nadir in a simplified transmission system integrated with real distribution feeders. By comparing GFL and GFM DER control methods, we evaluate the extent to which GFM DERs can contribute to stabilizing system-wide oscillations and improving frequency response. In addition to benefits, the paper also examines the potential adverse impacts of GFM DERs on distribution system protection.

[1] A. Venkataramanan, W. Wang, D. Ramasubramanian, A. Huque, T. Key, and A. Mehrizi-Sani, ‘‘Grid-forming distributed energy resources: Value in high renewable penetration and weak grid scenarios,’’ in Proc. 22nd Wind Sol. Integr. Workshop (WIW), vol. 2023, Sep. 2023, pp. 321–330.

The transition from synchronous machine-based generation resources to inverter-based generation sources marks a significant shift in the dynamics of modern power systems. Traditionally synchronous generators, which are inherently capable of providing essential grid support services such as frequency regulation, voltage control, and inertia, have been the backbone of electrical grids for over a century. As the penetration of inverter-based renewable energy sources increases, the grid's dependency on these inverter technologies grows. This shift necessitates new strategies and technologies to ensure that grid support services traditionally provided by synchronous generators are adequately replicated or replaced by inverter-based resources.

One critical aspect of inverter-based generation is its ability to provide frequency regulation. Synchronous generators contribute to frequency stability through their rotational inertia, which acts as a mechanical buffer against sudden changes in load. Inverter, however, can be equipped with advanced control algorithms that allow them to rapidly respond to frequency deviations, effectively mimicking the inertial response of traditional machines. This capability, commonly known as frequency-droop or frequency-watt, is crucial as it helps maintain the balance between supply and demand.

The global trend in renewable generation resources is shifting towards distribution-connected systems, as opposed to traditional transmission-connected systems. The IEEE 1547-2018 interconnection standard outlines the required frequency-droop capability of distributed energy resources (DERs), which is essential for maintaining grid stability. This capability allows inverters to autonomously modulate their power output in response to changes in grid frequency. Specifically, under high-frequency conditions, inverters are required to reduce their power output, while under low-frequency conditions, they should increase their power output, if possible. This dynamic response helps balance supply and demand, preventing frequency deviations that could lead to grid instability.

This paper describes the frequency-droop characteristics of IEEE 1547-2018 certified solar PV and energy storage inverters. Residential-scale PV inverter’s responses to grid over- and under-frequency conditions under various solar irradiance and active power limiting conditions are explained with test results. Energy storage inverter’s response to similar grid-frequency conditions under different operating modes (charging, discharging, and floating) will be shown. Proper understanding of smaller scale DER inverters’ grid frequency support capability will help system operators to properly configure and utilize the millions of these smart devices installed on the distribution circuits for system frequency stability.

In addition, transmission and distribution co-simulation analysis will be presented to demonstrate the importance of autonomous frequency regulation support from DERs on system frequency recovery after a transmission fault causing sudden drop in system demand. The paper will also include field performance of a transmission connected solar PV plus energy storage hybrid inverter’s frequency-droop control and potential impacts of restrictive interconnection rules.

Traditionally, black start and system restoration services have relied on large, transmission-connected synchronous generators, such as hydropower plants and fossil-fuel thermal stations. However, with the increasing decommissioning of conventional assets and the rapid growth of offshore wind capacity, alternative restoration strategies are required. This study investigates the feasibility of using offshore wind farms (OWFs), supported by battery energy storage systems (BESS), to deliver black start and system restoration services within the Scottish Power Energy Networks transmission network, with a specific focus on the restoration pathway toward Edinburgh and Glasgow.

A combination of resource configurations is assessed in line with the structure of the restoration services market in the United Kingdom. In the primary configuration, the BESS acts as the Primary Restoration Service Provider, responsible for establishing the voltage and frequency references following a blackout, in accordance with restoration service requirements. The OWF is evaluated in two roles: first, as a top-up restoration service provider that contributes active and reactive power support under a formal restoration contract; and second, as a conventional grid-following asset without a restoration contract, supporting the restoration process passively once the network has been stabilised. System performance is evaluated through detailed dynamic simulations, with particular emphasis on compliance with the Security and Quality of Supply Standard (SQSS) and relevant Grid Code requirements. Key metrics such as voltage regulation, frequency stability, short-circuit current contribution, and load pickup capability are analysed to validate the technical viability of the proposed configurations. The study demonstrates that offshore wind, when properly coordinated with fast-responding storage systems, can play a critical role in future restoration strategies, offering a resilient and sustainable pathway for black start services in high-renewable energy systems.

Executive Summary

Network codes for electric vehicle (EV) charging ensure efficient and safe integration of EVs into the power grid. These codes specify technical and operational requirements for grid connection, focusing on frequency and voltage stability, power quality, and certification. This paper evaluates the current implementation status of relevant requirements for EV charging throughout the world and compares the requirements of different grid codes. Compliance with these codes is crucial for manufacturers to meet product certification, thus enhancing reliability and market acceptance.

Motivation

Network codes establish technical standards and operational guidelines to ensure that electric vehicles (EV) can be integrated into the power grid efficiently and safely. For manufacturers, adhering to network codes is crucial. Compliance not only enhances system stability but also fosters market acceptance. Ideally network codes are streamlined as much as possible to facilitate the world wide EV market. The paper aims to provide a comprehensive understanding of network codes as perceived by the authors long standing experience in given development around the world.

Network code for electric vehicles

Network codes increasingly address electric vehicle charging. The following provides a summary of addressed requirements, including an evaluation of the current implementation state.

Frequency range

The frequency range defines the operational limits within which equipment must stay connected. It specifies the frequencies that equipment must be able to tolerate without any damage [1]. Typical ranges are ±2.5 Hz deviation from the nominal voltage for up to 30 minutes [4]. Since EV charging is inverter based, fulfillment does not pose major challenges to equipment manufacturers.

Rate of Change of Frequency

The Rate of Change of Frequency (RoCoF) is a measure of how quickly the system frequency changes, typically in the case of generation loss, expressed in Hz/s. Network codes specify RoCoF withstand capabilities to ensure that EV charging can remain connected and operational during such events[5]. Usual values are 4Hz/s for 0.25s [4] or 2Hz/s for 0.5s [2]. While inverters are capable of withstanding given values, proper testing is needed from a manufacturer’s perspective.

Limited frequency sensitive mode

Limited Frequency Sensitive Mode (LFSM) is an operational mode for power-generating modules that adjust active power output in response to significant frequency deviations. It includes LFSM-O (overfrequency), which reduces power output when the system frequency exceeds a certain threshold, and LFSM-U (underfrequency), which increases power output when the frequency drops below a specified level. Both are essential for maintaining grid stability during extreme frequency events by providing a rapid response to prevent system collapse [6]. Response occurs outside the normal operation window (typically ±200mHz), with a drop between 2-12% (typically 5%) [2][4]. In order to fulfill LFSM requirements, the grid frequency must be continuously monitored and reacted to, as is already state of the art.

Setpoint steps

Setpoint steps refer to the incremental adjustments made during the charging process. These steps ensure smooth transitions and prevent abrupt changes that could lead to system instability or equipment stress [7],

which is only a requirement in a few countries [2][3][4][12]. Gradual ramping is already possible with existing communication protocols and should be considered by smart charging providers, regardless of regulations.

Grid forming

Grid forming refers to the capability of inverter-based resources, such as electric vehicles, to establish and maintain frequency and voltage in the power grid, similar to traditional synchronous generators. This technology is essential for integrating inverter-based resources into grids with very few or even no synchronous generators. The inverters are controlled to behave as a voltage source, which enhances grid stability and provides inertia [8]. Not part of network codes yet, the European RfG draft sets this requirement for charging stations above 50 kW [4]. It will require adjustments to all newly installed fast charging stations. Although grid forming is in essence a control strategy, it will have to be properly understood and implemented by manufacturers.

Fault ride through / Voltage stability

Fault Ride Through (FRT) is the capability to remain connected and operational during periods of low voltage caused by faults. FRT requirements typically specify the duration and voltage levels that equipment must withstand without tripping [7]. Implementation for EV charging does not pose major challenges.

Reactive power range

The reactive power range specifies the limits in which the charging process is allowed to supply or absorb reactive power [2]. This range is defined in terms of kVA or as a percentage of the maximum reactive power capability. It will support the system to maintain voltage levels within acceptable limits under various operating conditions [9]. Albeit important to local system stability voltage ranges are not part of the RfG draft [4], although already required in some member states[2][12].

Voltage control

Voltage can be locally controlled through the adjustment of reactive power during the electric vehicle (dis-) charging process. Setpoints are either provided by the grid operator or based on a local voltage characteristic curve. For DC-charging above 12 kVA it is already a requirement in the German Network code [2]. For AC charging it is not yet required, since application would have to be done on the vehicle side, with varying requirements for different markets.

Harmonics

Harmonics in electrical networks refer to voltage or current waveforms that are multiples of the fundamental frequency, usually measured by the total harmonic distortion. Managing harmonics is crucial to prevent equipment overheating, reduce losses, and ensure the reliable operation of sensitive devices [11]. In case harmonics are regulated, the calculation follows specific formulas, not possible to cover in this chapter.

On board chargers of some electric vehicles are known for exceeding the set limits and have caused transformer failure at car dealerships in the UK, where numerous vehicles of the same brand are charged at the same main connection point.

Certification

Certification is process of verifying that equipment meets the specified technical and operational standards, introduced above [7]. Currently, most network codes only require a certificate of compliance from the manufacturer involved in the EV charging process, although testing requirements differ [2][4][12]. Independent testing is not done. Still, through self-certification legal accountability is ensured.

Further aspects

Within the paper, the general network aspects are elaborated by analyzing and comparing country specific setups of the network codes in key countries. Focus is given to the new European Regulation for Generators (RfG), and network codes from USA and China. In addition, the implication of smart charging on network code development is highlighted.

References

ENTSOE, https://eepublicdownloads.entsoe.eu/clean-documents/Network%20codes%20documents/NC%20RfG/161116_IGD_Frequency%20parameters_for%20publication.pdf, accessed on 2024-10-30

VDE, VDE-AR-N 4100, VDE VERLAG GMBH, 2019

VDE, VDE-AR-N 4105, VDE VERLAG GMBH, 2018

ACER, https://www.acer.europa.eu/documents/search?search_api_fulltext=ACER%20Recommendation% 2003 -2023, accessed on 2024-11-06

ENTSOE, https://eepublicdownloads.entsoe.eu/clean-documents/Network%20codes%20documents /NC%20RfG/IGD_RoCoF_withstand_capability_final.pdf, accessed on 2024-10-30

ENTSOE, https://eepublicdownloads.entsoe.eu/clean-documents/Network%20codes%20documents/ NC%20RfG/IGD_LFSM-O-U_final.pdf, accessed on 2024-10-30

ENTSOE, https://www.entsoe.eu/network_codes/rfg/, accessed on 2024-10-30

NESO, https://www.neso.energy/news/how-grid-forming-technology-changing, accessed on 2024-10-30

EURlex, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32016R1447, accessed on 2024-10-30

CLOUGLOBAL, https://clouglobal.com/voltage-fluctuation-vs-flicker-whats-the-difference/, accessed on 2024-10-30

WESCO INTERNATIONAL, https://www.anixter.com/en_us/resources/literature/wire-wisdom/an-overview-of-harmonics-in-electrical-systems.html, accessed on 2024-10-30

NORMA ITALIANA, CEI_0-21_2022 + amendments, 2022-2024

HUNTER LEWIS, presentation at https://mobilityintegrationsymposium.org/, 2024-10-07

In 2024, annual EV sales reached 22.7% of total vehicle sales in Europe. As we move closer to 2035, the de facto ban on the sale of new petrol and diesel vehicles will come into effect in some jurisdictions, creating even greater momentum around EV uptake. In local communities, the number of EVs will be largely commensurate with the number of dwellings. V2G could allow vehicles to plug and charge in their neighbourhoods, and also discharge, creating a relevant and available flexibility resource to balance the local network.

Smart charging allows consumers, who sit at the heart of the energy transition, to participate directly in providing flexibility. They can play an active role in relieving grid congestion, which lowers, in turn, the cost of electricity and increases reliability and security for users.

On balance, however, whether using V1G or V2G, smart charging offers a compelling economic justification. As identified in Eurelectric’s 2024 Grids for Speed study, making use of flexibility from available assets could contribute to a projected €4bn in savings every year for European grid operators. Combined with optimising the grid and anticipatory investments, flexibility can be considered part of a set of strategies to lower the overall grid investment cost from an anticipated €67bn to €55bn annually between 2025 and 2050.

The potential is huge. In terms of avoided curtailment of renewables, EVs could, in theory, contribute 4% of Europe’s annual power supply by 2030. Estimated at 114 TWh battery capacity, it is enough to power 30 million homes every year. And, by 2040, that potential becomes even more significant, as V2G could store more than 10% of Europe’s overall power needs and reinject when needed.

The economics of EV ownership will also improve where flexibility from unidirectional smart charging and V2G is optimised. Total cost of ownership (TCO) includes the cost of the vehicle, energy, tax, maintenance and insurance. Savings will vary by country and the electricity tariffs available. They will be informed by solar photovoltaic (PV) ownership, vehicle battery size, distance travelled and frequency of charge.

On a TCO basis, when the vehicle is optimally charged and benefits from V2G, EY estimates that the owner of a compact EV in the UK can save up to 19% (€1,270) annually compared with the cost of an internal combustion engine (ICE).2 In the large or sports utility vehicle (SUV) segment, the annual saving can be as much as 26% (€2,460). In Germany, Sweden and Spain, the TCO for a small vehicle could be reduced by as much as 14%. In France and the Netherlands, savings of 8% and 9% respectively may be realised.

Inevitably, using vehicle battery assets as a source of flexibility will bring challenges as well as opportunities. However, our conversations with industry leaders have allowed us to identify six prerequisites, which we explore in this study. They must be in place to unlock value from EVs as flexibility assets and support commercialisation.

Achieving climate targets requires not only expanding renewable energy but also electrifying the transport and the heat sector. As a result, increasingly high-power consumers such as electric vehicles and heat pumps are being increasingly connected to the grid. This is posing substantial challenges, particularly for distribution networks. Ideally, these loads should operate when renewable generation is abundant. Dynamic tariffs generally support adjusting load to generation, but they also increase the local grid load and provide no incentives for grid-friendly behaviour. To enable intervention, § 14a EnWG allows network operators to control or reduce flexible loads in the event of potential overload. In return, customers are compensated through reduced network charges for the controllable load. This paper investigates the economic potential of Vehicle-to-Grid (V2G) charging from the customer perspective, focusing on §14a EnWG Modules 1–3 and a hypothetical full grid fee exemption (Module 4). A new metering concept developed in the “BDL Next” project enables accurate separation of bidirectional energy flows for regulatory purposes and is incorporated into the model. Simulation results using the EBZ OptiTwin optimization model show that module choice has a significant impact on the economic efficiency of V2G applications, especially when no grid fee exemption is granted. In addition, there is a particular focus on regional differences. Due to the heterogeneous grid fees charged by the more than 700 network operators in Germany, the potential varies significantly. For that we present the “Germany Atlas”, a map of Germany with locally mapped potentials, which shows that the potential for V2G energy trading varies from minus 10 percent to plus 40 percent relative to a BDEW average grid fee, depending on the region in Germany

PVPS Task 16 aims to facilitate the integration of photovoltaic (PV) systems into energy grids by reducing costs and uncertainties related to solar resource assessment and forecasting.

The introduction by the Task Manager includes the overview, the specific work regarding grid integration: forecasting on different temporal and spatial scales and firm power studies. Additionally an outlook of the upcoming working areas will be presented (new phase of the project 2026-2029).

Regarding solar forecasting three approaches are investigated:

- Nowcasting based on All Sky Imagers

- Probabilistic forecasting

- PV power forecasting at different scales (e.g. for DSO's)

A benchmark of probabilistic forecasting was published; a benchmark of cloud based forecasts is currently written and a benchmark for numerical weather prediction based forecasts is planned for end of 2026.

Work on Firm Power is ongoing. Here we investigate the economic optimum between storage and curtailment or renewables.

A new report is foreseen for the end of 2025. The current state and overview of all studies done will be shown.

Additionally an outlook of the linked work in IEA PVPS Task 19 is given.

Energynautics contributed technical expertise to the World Bank–financed Rwanda Urban Mobility Improvement (RUMI) Project through its subcontract with Economic Consulting Associates (ECA). The study assessed the readiness of Rwanda’s energy sector to accommodate electric mobility, with a particular emphasis on battery electric buses (BEBs) at Kigali’s Nyabugogo Multi-Modal Transit Hub. Energynautics conducted an impact study on the distribution grid, including a hosting capacity analysis for large-scale bus depot electrification. In addition, a techno-financial analysis evaluated the potential cost savings of integrating rooftop photovoltaic (PV) systems with optional stationary battery storage at the transit hub. These main findings will be presented during the converence, as they provide actionable insights into infrastructure design and grid integration strategies for Rwanda’s transition towards clean, electrified public transportation. For further details can be taken from the report: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099741407092528476

There is an important question related to EV development about where the power will come from and what will be the implications in terms of matching supply and demand. There is also the important spatial dimension of demand and its impact on the electricity transmission and distribution system. This presentation and accompanying report will discuss the analysis of the impact of EVs in the case of Rwanda – following from a study carried out recently by Energynautics and Economic Consulting Associates (ECA) for the World Bank. The study assessed the impact of a range of types of EVs – from electric bicycles to light duty freight vehicles. It assessed the likely impact on power supply requirements for the period through 2050 under 3 different EV uptake scenarios – including on overall demand as well as peak demand. The presentation will also include the results of similar studies carried out for other geographies.

The increasing deployment of grid-forming (GFM) control in Type-IV wind turbine generators (WTGs) enhances frequency and voltage support but fundamentally alters electromechanical behaviour compared with conventional grid-following (GFL) operation. A key challenge is the excitation of lightly damped torsional modes (0.1–10 Hz), where rapid torque variations imposed by DC-link voltage regulation can oppose natural damping and amplify drivetrain oscillations.

This paper establishes the root mechanism of torsional amplification in GFM-WTGs through a simplified frequency-domain modelling framework and complementary phasor-domain insights. The analysis shows that, unlike in GFL operation where machine-side action reinforces natural damping, the GFM control architecture introduces an anti-phase torque component that can lead to weak or negative damping.

Theoretical findings are validated on a 2 kW hardware testbed, which reproduces a 2.5 Hz torsional mode under both grid- and wind-side disturbances. Experimental results confirm that torsional oscillations, self-damped in GFL operation, are strongly amplified in GFM mode, underscoring the practical significance of the identified mechanism.

Key contributions of this work are:

• Simplified modelling framework: A frequency- and phasor-domain approach that shows how GFM control introduces negative damping compared with the naturally damped GFL case.
• Experimental validation: Real-time hardware tests validate the proposed theoretical findings, adding practical credibility beyond simulation-only studies.

By clarifying the fundamental role of converter control architecture in shaping drivetrain dynamics, this work highlights the limitations of directly transferring GFL-based damping strategies to GFM systems. These insights provide a foundation for developing tailored mitigation approaches that ensure reliable and mechanically robust operation of future GFM-enabled wind energy systems.

The transition to renewable and fossil-free electricity generation is crucial to mitigate climate change. Solar photovoltaics (PV)

is the fastest-growing source of electricity globally, with many governments setting ambitious targets to increase PV capacity.

Unlike support schemes for utility-scale PV, wind, and hydropower, decentralized PV can be incentivised through mechanisms

targeting local energy communities.

Virtual self-consumption enables grid customers to collaborate and share the benefits of local, decentralised electricity generation.

Since 1 October 2023, Norway has allowed virtual self-consumption for grid consumers on the same property, primarily targeting

apartment buildings. A proposal for a broader virtual self-consumption scheme is proposed from 1 January 2026. This paper

evaluates the impact of virtual self-consumption on profitability of PV systems.

The proposed scheme offers increased benefits through reduced electricity consumption taxes and other grid fees, where applica-

ble. The results presented show how virtual self-consumption induce savings for > 4,000 Norwegian buildings, based on real-life

hourly smart metre data and simulated PV generation for the same locations. For large scale grid customers with capacity-based

tariffs, the scheme gives average savings equivalent to 31.2% of levelised cost of electricity for every kilowatt-hour virtually

self-consumed. For smaller scale grid customers with energy-based tariffs, the average savings per virtually self-consumed

kilowatt-hour are 61.8% of levelised costs of electricity. The savings on average reduces payback time with 6 years for large

scale grid customers and 22 years for small scale grid customers.

The rapid deployment of renewable energy is essential for achieving Europe’s climate and energy security objectives. However, without strong local support, social acceptance risks becoming a barrier to timely project development. This paper examines the drivers of public resistance - such as land use concerns, limited perceived benefits, and misinformation - and offers a practical framework to strengthen community support. Drawing on insights from developers and academia, it presents best practices for creating win-win outcomes through proactive community engagement and benefit-sharing measures tailored to local needs. Key success factors include trust-building, transparency, independence, adaptability, and long-term commitment. The paper also highlights the important role of policymakers in fostering supportive environments by streamlining permitting, enabling flexible legal frameworks, and linking renewable projects to visible local benefits, such as increased municipal revenues and economic opportunities.

This presentation introduces fast simulation methods for assessing harmonic compliance of inverter-based resource (IBR) plants that is necessary for receiving an energization (EON), interim (ION), and finale (FON), operational notification, for grid-connection of the IBR plants to the transmission grid. Generally, the harmonic compliance shall be proven by simulation studies applying harmonic impedance envelopes representing various operation regimes of the meshed transmission grid and provided by the grid operator.

The harmonic impedance envelopes may range from tens ohms up to several thousand ohms with a step by one ohm for each relevant integer harmonic and interharmonic order. Such studies shall be fully completed and approved by the grid operator prior to granting operational notifications.

Fastest-possible completion of the harmonic compliance studies and high accuracy of the results are essential for the IBR plant developers to obtain the operation notifications.

The first presented fast method allows expediting the simulation time by omitting slow processes by many repeated, embedded, load-flow and harmonic load-flow commands on large harmonic impedance envelopes with a required resolution. The method applies fast arithmetical operations on independent variables to identify the area within the harmonic impedance envelope with the largest harmonic voltages and then, reduce the number of the embedded commands to be executed. The first method reduces the simulation time up to 65 times with the largest benefit for the largest envelopes.

The second fast method applies interpolation through critical points within the envelope to calculate the largest harmonic voltage. The second method simulates up to 20 times faster than the first method.

The third fast method combines the two first methods. This presentation will demonstrate the three methods using anonymized, real-life, examples and propose possible areas of applications.

Fast outer-loop voltage controllers are commonly implemented in energy parks to regulate voltage and reactive power at the point of connection (POC). Operating similarly to plant-level Power Plant Controllers (PPC), these are often utilised in synchronous condenser installations, hybrid generation plants, and renewable energy projects. This paper presents outcomes of a recent Australian project examining coordinated tuning of synchronous condenser excitation systems, fast outer-loop voltage regulators, and conventional Power System Stabilisers (PSS). Driven by grid codes that demand rapid voltage and reactive power response at the POC, the study evaluates the practical implications and stability risks introduced by aggressive control strategies. Specifically, fast outer-loop voltage controllers impose challenging bandwidth requirements on automatic voltage regulators (AVRs), which can compromise small-signal stability and reduce the damping provided by conventionally tuned PSS.

A particular focus is the adverse interaction arising when fast outer-loop voltage regulators introduce biases at the AVR summing junction, typically shared by PSS signals based on rotor speed and active power. This configuration inherently alters PSS behaviour and phase compensation requirements, reducing damping effectiveness or causing unintended oscillations. To quantify these interactions, RMS-based simulations employing Fourier-based sinusoidal injections at the POC were conducted. Frequency-domain assessments illustrated through Bode plots clearly reveal resonances and identify critical frequencies where outer-loop control negatively impacts damping performance. Eigenvalue analyses complement these results, validating the observations.

The study identifies that integrating dead bands within fast outer-loop controllers is essential to minimise unnecessary controller interventions and reduce adverse interactions with inner-loop AVRs and PSS. Additionally, conventional PSS must be carefully retuned or fully redesigned when operating alongside aggressive outer-loop controllers, particularly if assessed against rapid voltage response criteria measured at the POC. Instead, it is recommended that voltage response and settling-time criteria be evaluated directly at machine terminals. Time-domain simulations and eigenvalue analyses demonstrate superior stability and voltage regulation performance from deliberately slower outer-loop controllers.

Practical guidelines for coordinated tuning strategies, strategic use of dead bands, slower outer-loop controllers, and appropriately retuned or redesigned PSS are provided. These recommendations enhance overall system stability, improve damping, and optimise voltage performance in grids dominated by variable renewable energy sources.

The number of photovoltaic (PV) installations is increasing. Within 2024, an additional 16.2 GW of PV capacity was installed

in Germany. In total, the majority of installed systems are connected to the low-voltage grid and mounted on rooftops. This

development marks a structural shift from passive, radial grids to networks characterized by volatile renewable generation. As a

result, low-voltage grids experience increasing bidirectional power flows and more variable net injections at the grid connection

points. Since PV is expected to remain a central pillar of the transition toward a carbon-free energy system and in meeting

the 1.5°C climate target, associated issues - such as grid congestion and voltage band violations - are expected to intensify.

Consequently, accurate forecasting of the grid state is essential for distribution system operators (DSOs) to enable proactive and

preventive grid management. This work presents a real-time system for nowcasting the state of low-voltage distribution grids

using open-source approaches, developed and validated with reference to a real German distribution grid in Hittistetten. The

grid model is kindly provided by the local DSO, Stadtwerke Ulm/Neu-Ulm Netze GmbH, to the Smart Grids Research Group

as a representative test area, with measurement data available from various grid components. The objective is to demonstrate a

forward-looking methodology that enables DSOs to maintain reliable and stable grid operation under increasing PV penetration.

The core of the system is a solar radiation forecast based on data from the Meteosat Second Generation (MSG) satellite. This feeds

into a physical PV power model to generate feed-in forecasts for the grid area. A complementary load forecast is generated using

modified standard load profiles. These feed-in and load forecasts are combined and processed through a load flow algorithm to

determine the future grid state. Because the load profiles are based on annual aggregates, the load forecast is further refined using

real-time measurements of transformer utilization. The complete model chain is comprehensively validated using measurement

data from the operational grid. All components of the model show strong correlation with observed data and low prediction

errors. The system provides accurate PV generation forecasts and, at an aggregated level, reliable grid status predictions for two

out of three transformers in the test network. This study demonstrates that data-driven nowcasting of the low-voltage grid state is

not only technically feasible but also represents a key contribution to ensuring grid stability amid the evolving dynamics of the

energy system, ultimately enabling DSOs to perform active grid control.

Electrifying sectors like land transport and building heating is a cost-effective strategy for decarbonisation. For harder-to-abate sectors that require fuels for their density or chemical properties, like long-haul aviation, shipping, backup power or iron ore reduction, electrolytic hydrogen and its derivatives are often proposed as part of a ‘hydrogen economy’. However, hydrogen itself is challenging to transport and store because of its small molecule size and low volumetric density; the build-up of a pipeline network needs close coordination with demand, supply and storage. We present a ‘minimal methanol backstop’ as an alternative concept for filling the gaps that high electrification scenarios cannot reach. As a liquid in ambient conditions, methanol is easy to transport and store; it scales down to low-volume use cases without the lumpiness of hydrogen pipelines; it is a better drop-in fuel to replace methane in turbines; it can help integrate decentralised biomass wastes and residues into the energy system; it can be used as a feedstock for industry and transport fuels. We show in an energy system model for Europe that deep decarbonisation has lowest cost when hydrogen can be widely transported and used for backup power, but a methanol-based system is only 11 billion euros per year more expensive (1.3% of system costs) with default model settings. This increase stays below 5% in all sensitivity runs that we considered, with the highest increases occuring in settings with lower electrification, higher carbon dioxide sequestration and relaxed carbon dioxide targets. We argue that this modest expense is justified because methanol avoids many of the challenges in scaling up and regulating hydrogen infrastructure.

The European power system is transitioning toward a higher share of variable renewable energy sources. As a result, the task of ensuring power system balance becomes increasingly challenging due to the inherent variability and forecast uncertainty of these resources, highlighting the need for robust methods to assess and quantify system flexibility. This study explores how future balancing and flexibility needs can be assessed using the Balancing Tool Chain (BTC), a multi-stage modelling framework linking long-term planning, day-ahead scheduling, hour-ahead balancing, and real-time frequency control. By capturing interactions between forecast errors, dispatch decisions, and resource availability, BTC enables consistent analysis of future balancing challenges.

A case study of the Nordic power system for 2030 is conducted to quantify regional flexibility needs by comparing updated hour-ahead wind forecasts with day-ahead dispatch schedules. This approach identifies net imbalances and available regulation capacity across technologies and areas. The results highlight large regional differences in flexibility requirements, with hydro reservoirs providing stable balancing capacity, while wind-dominated areas face frequent uncovered needs and rely heavily on cross-border exchanges. The findings demonstrate the need and value of integrating balancing market modelling with long-term planning to support the electricity market development and system design.

Power system oscillations pose a significant influence on power grids and may potentially result in instability and blackouts. Traditional solutions for damping these oscillations include power system stabilizers (PSS) associated with synchronous generators and Flexible AC Transmission Systems (FACTS) devices [1,2]. However, as renewable energy sources replace conventional power plants, the PSS based on synchronous generators is no longer feasible. Consequently, damping power system oscillations in large systems, e.g. Entso-E system, with a large share of renewable energy sources is becoming a challenging task, e.g. the low-frequency oscillation before the blackout in Spain on 28.April 2025 shown in Fig. 1 [3].

Fig. 1. Power system oscillation before the blackout in Spain on 28. April 2025

Based on the measured data from Gridrada [4], this paper investigates the oscillations before the blackout in Spain and Portugal, as shown in Fig. 2.

Fig. 2. Power system oscillations before the blackout in Spain and Portugal

The study employs modal analysis to evaluate the interactions in the EU network and the eigenvalues are shown in Fig. 3.

Fig. 3. Eigenvalue analyses

The results of this paper underscore the importance of grid-forming controls of renewable generation in ensuring the reliability of modern power systems under the global energy transition.

References

[1] P. Kundur, Power System Stability and Control, McGraw-Hill Education Ltd, ISBN-10:‎ 007035958X.

[2] G. Rogers, Power System Oscillations, Springer, 978-1-4615-4561-3.

[3] https://www.linkedin.com/posts/philippe-jacquod-76227a5_time-will-tell-what-circumstance-or-chain-activity-7322729833828945920-HS44/

[4] https://gridradar.net/en

There is an increasing need to perform real-time simulation of power plant performance behaviour using Hardware-in-the-loop (HiL) and/or Software-in-the-loop (SiL), particularly for HDVC grid connected wind power plants. Real-time simulation based on HiL/SiL can help mitigate grid connection challenges by allowing more realistic testing of the target system under different grid, weather and operational conditions, which is either impossible or costly to do on-site; hence, HVDC and wind power plants can be largely de-risked before connecting to the grid and start of operation. In this paper, the methods to develop source code based SiL models (same control code as in real products, such as Wind Turbine Generator) are investigated. Two main real-time simulation platforms are considered, i.e., RTDS and OPAL-RT. A common SiL execution platform based on IntervalZero is introduced, which can interface with both RTDS and OPAL-RT and thus, largely improve the interoperability and scalability of SiL models. In the end, a comparison between HiL and SiL models and between the SiL and PSCAD (offline) models are presented, including discussions about the intended use scenarios of real-time and offline simulation.

Studies looking at electricity market designs for very high shares of wind and solar often conclude that the energy-only market will break down. Without fuel costs, it is said that there is nothing to set prices. Symptoms of breakdown include long phases of zero prices, scarcity prices too high to be politically acceptable, prices that collapse under small perturbations of capacities from the long-term equilibrium, cost recovery that is impossible due to low market values, high variability of revenue between different weather years, and difficulty operating long-term storage with limited foresight. We argue that all these problems are an artefact of modelling with perfectly inelastic demand. If short-term elasticity to reflect today’s flexible demand (-5%) is implemented in the model, these problems are significantly reduced. The combined interaction of demand willingness to pay and storage opportunity costs is enough to produce stable pricing. This behaviour is illustrated by a model with wind, solar, batteries, and hydrogen-based storage, where the price duration curve is significantly smoothed with a piecewise linear demand curve. This removes high price peaks, reduces the fraction of zero-price hours from 90% to around 30%, and guarantees more price stability for perturbations of capacity and different weather years. Fuels derived from green hydrogen take over the role of fossil fuels as the backup of final resort. Furthermore, we show that with demand elasticity, the long-term optimisation model exactly reproduces the prices of the short-term model with the same capacities. We then use insights from the long-term model to derive simple bidding strategies for storage so that we can also run the short-term model with limited operational foresight. We demonstrate this short-term operation in a model optimised using 35 years of weather data and then tested on another 35 years of unseen data. We conclude that the energy-only market can still play a key role in coordinating dispatch and investment in the future.

- Energy-only markets can remain functional with 100% zero-marginal-cost wind & solar.

- Price bifurcation to zero & high levels is an artefact of perfectly inelastic demand.

- With demand elasticity, zero-price hours reduce from 90% to 30% of the time.

- Demand elasticity stabilises prices for many years and capacity perturbations.

- Demand elasticity allows identical price formation in investment and dispatch models.

This work has been published in Energy Economics: https://www.sciencedirect.com/science/article/pii/S014098832500307X

A preprint is available here: https://arxiv.org/abs/2407.21409

Decarbonisation, decentralisation, and intermittency are driving the development of flexibility markets towards shorter market time units (MTU). Shorter MTUs and shorter gate closures lower the entrance barriers of demand side aggregators that face significant uncertainty on longer time scales. We study the business case for aggregated EV fleets participating in the Nordic 15-minute mFRR Energy Activation Market (EAM). Motivated by increasing system granularity and rapid EV uptake, we represent fleet flexibility as a virtual battery with time-varying power and energy envelopes and formulate a risk-aware stochastic optimisation that co-ordinates day-ahead scheduling with quarter-hour mFRR bidding. Using synthetic residential charging cohorts and observed day-ahead prices on two stylised days, we compare an independent day-ahead baseline to a co-optimised strategy under conservative availability and a CVaR-augmented objective. Across both price cases, co-optimisation increases expected profit and lowers downside risk: the model buys less energy day-ahead and shifts procurement toward mFRR down while flattening the charging plan to retain eligibility for mFRR up. Profit decomposition shows that the uplift is driven by higher mFRR down revenues and reduced reliance on unwinding day-ahead positions. We discuss operational implications for bidding and outline two extensions: rolling 45-minute re-optimisation and a V2G framework.

Converters with grid-forming properties will cover a part of the demand for voltage source behavior and thus play an essential role in ensuring power system stability. However, this demand will not be fully met by the transmission system operators' own assets with grid-forming properties, i.e. HVDC converters and STATCOMs. Customer facilities at extra-high, high, and medium voltage levels with grid-forming capabilities will play a key role in meeting the power system’s demand for such properties and significantly shape system dynamics.

The absence of clear guidelines for ‘grid-compatible behavior’ and the resulting interpretive flexibility in the development of grid-forming facilities have led to a wide variety of implementation approaches. While grid-forming converters replicate key characteristics of synchronous generators - particularly voltage source behavior - they do not inherently emulate their dynamic behavior. Unlike synchronous generators, whose dynamics are defined by its physical laws, the behavior of grid-forming converters is mostly defined by its control algorithms. Therefore, it is essential to assess the current state of development across different concepts to accurately reflect their system behavior in future studies and, if necessary, adapt requirements and verification procedures for market-based procurement or grid connection requirements.

In a project of the four German transmission system operators (TransnetBW, 50Hertz, Amprion and Tennet) and Fraunhofer ISE, a verification procedure and a catalog of requirements for grid-forming behavior were developed with the participation of various converter manufacturers. The anonymized comparison and determination of the state of the art of grid-forming converters are the main objectives of this project. Important lessons were learned for future verification procedures and requirements and conclusions were drawn as to where these need to be refined or expanded.

This presentation outlines the project's background and highlights its potential benefits for TSOs, manufacturers, and testing laboratories. It concludes with a summary of the key elements of the developed testing and laboratory procedures.

The transition to electric vehicles poses challenges for power system planning, particularly in distribution grids. This paper introduces a novel method for simulating electric vehicle driving trips at scale to model realistic driving behaviours. By incorporating empirical mobility patterns into the simulation environment, the approach enables detailed analysis of temporal and spatial charging demand. Integration with the SIMONA framework facilitates co-simulation with the electric power system, allowing power flow calculations and load management strategies. Validation against real-world data demonstrates high accuracy in predicting parking duration across various states while identifying deviations affecting energy consumption profiles. An exemplary scenario highlights significant grid impacts from electric vehicle charging infrastructure. The presented open-source MobilitySimulator supports forecasting charging demands, optimizing grid investments, and evaluating smart charging strategies to mitigate negative grid effects and enhance renewable integration. This scalable methodology advances research on grid interactions with electric vehicles and sustainable power systems planning.

Part of a possible Grid-Forming-Benchmarking-Project-Session

Converters with grid-forming properties will cover a part of the demand for voltage source behavior and thus play an essential role in ensuring power system stability. However, this demand will not be fully met by the transmission system operators' own assets with grid-forming properties, i.e. HVDC converters and STATCOMs. Customer facilities at extra-high, high, and medium voltage levels with grid-forming capabilities will play a key role in meeting the power system’s demand for such properties and significantly shape system dynamics.

The absence of clear guidelines for ‘grid-compatible behavior’ and the resulting interpretive flexibility in the development of grid-forming facilities have led to a wide variety of implementation approaches. While grid-forming converters replicate key characteristics of synchronous generators - particularly voltage source behavior - they do not inherently emulate their dynamic behavior. Unlike synchronous generators, whose dynamics are defined by its physical laws, the behavior of grid-forming converters is mostly defined by its control algorithms. Therefore, it is essential to assess the current state of development across different concepts to accurately reflect their system behavior in future studies and, if necessary, adapt requirements and verification procedures for market-based procurement or grid connection requirements.

In a project of the four German transmission system operators (TransnetBW, 50Hertz, Amprion and Tennet) and Fraunhofer ISE, a verification procedure and a catalog of requirements for grid-forming behavior were developed with the participation of various converter manufacturers. The anonymized comparison and determination of the state of the art of grid-forming converters are the main objectives of this project. Important lessons were learned for future verification procedures and requirements and conclusions were drawn as to where these need to be refined or expanded.

The presentation will detail the testing and laboratory procedure, followed by key results from the measurement campaign. The focus lies on the first two aspects of the procedure: ‘Voltage Source Properties’ and ‘Inertial Response’.

Grid design and battery integration for industrial microgrids pose significant challenges due to fluctuating loads and the intermittency of renewable energy sources. Preliminary frontend engineering and design (preFEED) enables cost-effective assessments based on high-level system modelling. This study introduces a techno-economic preFEED framework tailored to industrial microgrids, with a focus on battery energy storage systems (BESS) that balance energy shifting and grid stability under uncertainty. The framework emphasizes cost-optimal operation while incorporating grid-stability considerations, drawing insights from a comprehensive meta-study on microgrid design. We apply our framework to a mining use case, in which electrification by means of renewables and battery energy systems shall reduce the carbon footprint and contribute to more sustainable mining. Our results show that complex and costly FEED design can be streamlined through an interactive and user-friendly preFEED approach, enabling early-stage techno-economic evaluations. This methodology serves as a practical entry point for site managers and facilitates informed decision-making for a transition to low-carbon industrial site operation.

The InterBDL joint project, funded by the Federal Ministry for Economic Affairs and Energy and led by Ulm University of Applied Sciences (THU), is investigating the interoperability of bidirectional charging of electric vehicles. The central research goal is the seamless integration of electric vehicles into existing energy supply systems through systematic analysis of the entire charging and discharging process chain. The innovative research approach comprises a comprehensive investigation using a multi-level test environment: simulations, laboratory experiments and field tests. Particular focus is placed on the use of open standards at system interfaces to ensure optimal communication between electric vehicles and energy systems. The research analyses technical, economic, regulatory and socio-cultural aspects. The aim is to develop concrete recommendations for action for stakeholders from politics, regulation, standardisation, industry and research. To this end, THU is developing a comprehensive system test that holistically evaluates all project functions. This integration test checks bidirectional charging power, energy flow control and communication protocols, and also compares the performance of different charging technologies.

“Iberian Peninsula blackout: analysis and performance of Nordex wind power plants”

The topic presented in the paper will show the analysis and performance recordings registered on Nordex wind power plants during the Iberian Peninsula blackout happened last April 2025.

On Monday April 28th at 12:33 PM, an unprecedented blackout affected the entire Iberian Peninsula, including Spain, Portugal and a small part of south-west France. This event was the first "zero energy" case in the Iberian region's history.

Firstly, the paper will analyze what was the Iberian grid situation before the blackout, the high penetration of renewables (70%) and the system inertia values observed. Moreover, an overview on power oscillations observed 30 and 10 min before the event will be included. The oscillations affected the whole European continental grid and were correctly controlled and dampened. However, power oscillations were not seen during the blackout, so they could be not directly related to it.

Secondly, the paper will summarize what was the sequence of events. The blackout was caused by a cascade disconnection of generation plants in the southern and western regions of Spain. This cascade disconnections of generation power plants caused a significant power imbalance, making the grid frequency decrease to less than 47Hz in less than 5s and RoCoF to less than -4Hz/s, what motivated the disconnection from the European continental grid and from Morocco and finally caused the complete collapse of the Iberian electrical system.

Entering more technical details, the paper will compare ENTSO-e and REE published sequence of events with the recordings from one of the Nordex’s wind power plants operating close to where the blackout was originated. The detailed graphical comparison of the voltage and frequency recordings available from 20s before the blackout until the system collapse will show a significant match with the sequence of events declared by REE and ENTSO-e.

The root cause analysis investigation done by REE and Spanish government is still ongoing, and new small pills of information are released every week. The paper will summarize the official information available. In the moment of this abstract presentation, the main root cause of the blackout was a cascade of disconnecting of generation plants due to overvoltage. Discussions regarding the responsibility of the wrong voltage control are on-going between the main Spanish electrical energy companies, REE and local distribution system operators. Moreover, the power generation spinning reserve planned by REE for that moment seemed to be not enough to compensate the unexpected big loss of generation. Other possible hypothesis like an unusual atmospheric phenomenon, cyberattack or lack of inertia due to the big share of renewables seem to be discarded.

Finally, the paper will show how Nordex wind farms operated during the event, injecting all available power from the wind during all the event and only disconnecting when the grid voltage and frequency went out from the operating ranges required by the grid code and the whole system collapsed. In addition to this, an overview on the historical use in Spain of existing system services of Nordex wind power plants like voltage control or spinning reserve will be shown, offering existing and future solutions that Nordex’s wind power plants could provide to prevent from similar blackout events in the future.

Wind energy is the most important renewable energy source in Germany. To effectively integrate wind power into the energy system, it is essential to understand both the temporal and spatial characteristics of wind power feed-in on a micro- and large-scale.

While existing approaches for large-scale yield calculations often rely on simplified models that overlook microscale losses, this study presents a novel approach that integrates microscale loss calculations while still enabling simulations on a national scale.

For this purpose, a fully automated model chain was developed that utilizes various high-resolution spatial and temporal input data, combines them with loss calculation models, and returns specific losses and yields for individual wind turbines.

The models were applied to onshore wind turbines in Germany, using a wake loss model and a model for losses due to bat curtailments. Simulation results show that the model chain enables calculating large-scale losses based on microscale loss calculations. A comparison of losses between different federal states in Germany shows that the importance of different loss types exhibits strong regional variations.

The developed model chain is suitable for a wide range of use cases, especially for the simulation, planning and optimization of energy systems on regional and local scales.

Vehicle-to-Grid (V2G) technology enables bidirectional energy flows between electric vehicles and the power system, supporting grid stability, renewable integration, and new value streams. Yet, large-scale deployment is hindered by fragmented system architectures and limited interoperability across technical and market domains.

This paper presents a consolidated V2G architecture that integrates both behind-the-meter (BTM) and in-front-of-the-meter (ITM) perspectives into a unified framework. By synthesizing prior projects with different focus areas, the blueprint provides a holistic representation of roles, devices, and interfaces along the V2G chain. The results highlight how interfaces between EVs, charging infrastructure, energy management systems, and aggregators must align with standards such as ISO 15118, OCPP, and IEC 61850 to ensure scalable interoperability.

Key findings show that standardization gaps remain, particularly for bidirectional use cases, semantic harmonization, and BTM-specific integration. Furthermore, reliable data with sufficient frequency, accuracy, and trustworthiness is essential for enabling V2G participation in flexibility markets.

Developed within the BMWK-funded project InterBDL under the lead of IE2S, the consolidated blueprint is positioned as a living reference. Its upcoming publication for public consultation aims to validate and refine the model, thereby advancing the path toward interoperable and market-ready V2G solutions.

The increasing share of intermittent renewable energy sources, the phase-out of controllable power generation units, and changes in electricity consumption behavior are significantly transforming the electric power system. By 2035, these changes will require greater flexibility from the demand side to ensure grid stability, particularly in Europe. Historically, domestic loads have contributed to frequency and voltage stability through their natural sensitivity to grid conditions. However, the widespread adoption of power electronics in consumer devices has diminished this inherent sensitivity.

This research project focuses on leveraging local electrical measurements to reintroduce automated and autonomous responsiveness in electric vehicle (EV) charging to enhance grid flexibility. Specifically, the project aims to develop a smart charging cable that modulates the EV charging power based only on local grid parameters such as voltage amplitude and frequency. This solution is particularly relevant for existing alternating current (AC) charging infrastructures (mode 3, single or three-phase), offering backward compatibility on existing charging station without requiring user intervention or centralized control.

The proposed system uses a hardware “man-in-the-middle” approach to dynamically adjust the control (CP) signals exchanged between the EV and the charging station. By altering this signal in real-time based on local voltage and frequency measurements, the cable can autonomously limit the charging power in response to grid disturbances, frequency deviations, or voltage reductions before for example activating the Load Frequency Demand Disconnection.

The methodology combines both scientific and technological components. Scientifically, it involves the development of an algorithm that determines optimal power limitation levels based on local grid conditions. Technologically, an LFSM-UC algorithm is integrated into a prototype smart cable that interfaces directly between any standard AC charger and an EV, ensuring real-time responsiveness without relying on telecommunications networks. This architecture provides robustness against communication failures, enhances grid stability, and minimizes environmental impact from additional infrastructure.

Preliminary lab tests using an EV emulator and several EV from different manufacturers confirm the cable's ability to quickly adjust charging power based on predefined voltage and frequency thresholds. The results demonstrate the feasibility of decentralized demand response in EV charging and offer a scalable, user-transparent solution to support future grid stability requirements.

The energy transition in Europe and other parts of the world is characterized by the development and deployment of renewable energy sources such as wind- and solar power. In recent years, the transformation and conversion of renewable energy into sustainable solutions like Power-to-X (PtX), especially hydrogen or e-methanol (but also others), has become more and more important and plays a key role in achieving the decarbonization targets of the energy system. In recent years, many large-scale PtX projects have been announced and discussed, but only a few of them have been realized and are in operation.\\

This paper focuses on the Grid Compliance aspects of co-located generation and demand facilities, mainly based on the example of the Kassø PV + PtX plant in Denmark. The work will briefly introduce the requirements applied to co-located plants in Europe and Denmark (especially NC RfG and NC DCC and upcoming updates) and will outlines challenges during the grid compliance process in the areas of design (grid related capabilities and functionalities), simulation model development and assessment of the simulation results (RMS- and EMT models) as well as grid compliance testing. Furthermore, the paper will provide lessons learned and recommendations for future requirements for co-located facilities.

In modern power systems, the increasing integration of converter-based renewable energy sources and dynamic load behaviors necessitates real-time assessment of small-signal stability. Traditional stability analysis could be computationally intensive for real-time applications. This paper proposes a methodology to evaluate small-signal stability based on operating conditions using a regression model that correlates a damping-ratio-based stability index to system parameters via polynomial regression. The resulting polynomial function is designed to serve as an additional constraint in a unified single-step small-signal stability-constrained optimal power flow (S3C-OPF) formulation, enabling stable and optimal solutions. To ensure compatibility with optimal power flow (OPF) solvers, the model is constructed to be convex, continuous, and twice-differentiable. A multi-stage regression approach is employed: the first stage fits a polynomial model, and the second enforces convexity through eigenvalue clipping and linear regression. The training dataset is generated using Latin Hypercube Sampling, followed by OPF computations to ensure operational feasibility. The methodology is validated on a modified IEEE-9 bus AC system. Results show high prediction accuracy, with root mean squared error (RMSE) of 0.04 and misclassification rates below 1%. Convexification preserves model accuracy, while ensuring convergence when integrated into an OPF framework. The proposed approach could be utilized for real-time operations and replace computationally intensive simulations during real-time operations.

This final presentation of the GFMC benchmarking project focuses on ‘Support to power quality’, the ‘Operation during critical grid events’ and the avoidance of unwanted ‘Controller interactions’. As in Part II, the testing and laboratory procedures will be outlined, followed by the most relevant results from the measurement campaign.

The share of electric vehicles is planned to increase to more than 90% in the year 2045. Consequently, the capacity of the energy grid must be accordingly extended. For predicting future loading needs in the cities of Ulm [KD1] / Neu-Ulm (Germany) and projecting them onto the existing energy grid, a tool chain has been realized, described herein. The resulting simulation system computes the charging needs and interactions between the grid and the vehicle fleet on a disaggregated level of single vehicles, their stops – locations and durations –, and single lines from the cities’ energy grid. The results are assumed to help the authorities responsible for the energy grid to plan necessary extensions.

The growing share of renewable energy sources increases the need for demand-side flexibility. Large-scale water electrolysers can support electric grids while reducing hydrogen production costs. Their participation in ancillary markets offers a dual benefit: grid stabilization and reduced cost for renewable hydrogen.

Existing studies on grid integration of electrolysers often use simplified dynamic models that overlook essential physical characteristics of the stacks. In particular, the influence of balance-of-plant (BoP) equipment, which governs temperature dynamics, is frequently excluded. When BoP modelling is not included, parameters such as the hydrogen-to-oxygen (HTO) ratio during dynamic operation is overlooked, even though it is relevant to operational safety. In this work, we present a Simulink model that integrates power electronics with detailed process dynamics of an electrolyser plant, explicitly including balance of plant (BoP) components. The model is used to evaluate performance of electrolyser plant, applying standardized testing protocols from the QualiGrids project to replicate prequalification requirements for frequency containment reserve (FCR) services.

Simulation results show that the electrolyser plant meets the required KPIs on power stability, ramp duration and initial response time. However, dynamics of HTO ratio evolve more slowly than power responses and has cumulative effect during prolonged operations, highlighting the importance of continuous gas ratio monitoring. This highlights the value of detailed dynamic modelling for safe and reliable operation of electrolyser plants in balancing markets.

This paper presents the role of the EEBUS Initiative e.V. in the InterBDL research project, which focuses on the development and validation of interoperable use cases for bidirectional electric vehicle (EV) charging. The project addresses the entire communication chain, spanning market actors, grid operators and household charging infrastructure, with the aim of enabling new digital energy services. Within InterBDL, EEBus leads Work Package 7, dedicated to the integration of local energy resources via the smart meter gateway (SMGW) infrastructure and standardised communication interfaces. Building on the established EEBUS Use Case framework, the work promotes harmonisation and contributes to standardisation in national and international committees. Testing activities are carried out in the EEBUS Living Lab Cologne, which enables cross-partner interoperability validation under realistic conditions. Beyond the development of interoperable use cases, the project specifically targets the seamless local integration of charging infrastructure (LIS), energy management systems (EMS) and iMSys infrastructure (control units, SMGW and backend). By relying on freely accessible, standardised specifications and interfaces, the project reduces complexity and supports the creation of scalable, market-ready and user-friendly solutions

A large number of field FRT tests are already carried out with the test setup "Transformer cut in". As part of the OptiTransient research project, experiments have been carried out as an example on a grid forming inverter and compared with other possible test facilities. In addition to the usual amplitude changes or vector angles jump by coupling a length impedance the angle jump were also generated by the triangular switching of the coils. At no load, the voltage have a clean characteristics. Under load, the impedances influence the test subject.

Especially with simulation of transformer switching groups B and D without a supplementary Dy transformer, asymmetrical impedances and thus asymmetrical feed -in occur. Converters are particularly sensitive to unsymmetrical impedances.

Until now, steps-tests for "Transformer Cut In FRT-Tester" can not be feasible as a limit. Analyzes from the OptiTransient research project show that real grid drops often followed by an over voltage event after grid recovery. Step tests can realized with additional impedances which limited circular current.

The tests will be challenging if no further additional impedances are to be used from financial and practical considerations. Such tests can be carried out in the limited area with previously excluded turning closure.

Results will be shown to the various test facilities. The respective limits of the test facilities will also be discussed.

For the "Auto Transformer Cut-in", the integrated coil requires a special equivalent circuit diagram of the test device.

The mathematical relationships should be discussed and compared with the measurements.

Grid-forming (GFM) control is expected to play a key role in the renewable energy transition, with Virtual Synchronous Machine (VSM) control emerging as a leading solution. VSMs allow converter-based sources like wind turbines to emulate synchronous generator behaviour by providing inertia and damping. However, extracting additional power during frequency disturbances causes rotor deceleration and increased current demand, which can push the turbine into stall or exceed semiconductor current limits—ultimately constraining energy extraction and reducing performance. This trade-off is often overlooked in existing research. This paper investigates optimal VSM tuning across the full wind turbine operating range, considering both energy constraints and UK grid code requirements. In the 4–7m/s wind speed range, the dominant constraint is rotor stall due to excessive deceleration from high VSM gains. At higher wind speeds, converter current limits become more restrictive, as baseline output leaves less margin for additional power injection. Simulations using a 10MW wind turbine model in MATLAB/Simulink demonstrate the impacts of optimal VSM tuning over the full wind turbine operating range, including improved inertial response but also highlight extended rotor recovery and increased exposure to damaging structural frequencies. These results open a wider discussion about wind turbine operating strategies and market incentives to increase inertial support.

The global shift toward a sustainable energy future has significantly changed the landscape of power generation, replacing a growing number of large, centralized conventional power plants with an increasing amount of smaller, decentralized energy resources. This transformation introduces both opportunities and challenges for maintaining power system stability—particularly in light of the increasing share of converter-based generation. In this evolving context, grid-forming inverters have gained prominence as a core technology to support stable operation in power systems with up to 100% renewable penetration. These inverters not only function as controlled voltage sources, but can also provide synthetic inertia and strengthen the grid.

With the latest development of new regulations and testing guidelines in Germany, the integration of grid-forming inverters becomes more tangible (see “VDE FNN Hinweis – Technische Anforderungen an netzbildende Eigenschaften inclusive der Bereitstellung von Momentanreserve Version 2.0 Mai 2025”). The properties, requirements and behavior of grid-forming systems are now described in more detail in the latest version of the document. In the document, the desired grid services, such as the behavior in the event of defined frequency changes (RoCoF), phase angle jumps or short circuits (FRT) are addressed by corresponding requirements for grid-forming converters.

In particular, the requirements in the RoCoF and phase angle jump case are specified from the perspective of “normal operation” of grid-forming converters. However, grid-forming converters are subject to strict limitations, such as maximum current, and are therefore equipped with current limiting procedures. Depending on the realization of the current limiting procedures, these have a significant influence on the system behavior of the grid-forming converters during current-limiting operation in the highly dynamic and longer-term time range.

The paper examines and discusses the requirements listed in the “VDE FNN Hinweis” for various dynamic events under the influence of the current limiting operation of grid-forming converters. Laboratory tests of a grid-forming converter, which is tested and evaluated by a grid simulator according to the RoCoF, phase angle jump and a fictitious islanding test case, are analyzed. Conclusions are then drawn on the effects of current-limiting operation on the required grid services.

This paper provides a practical overview of the various processes that enable a collaborative exchange of simulation models across independent simulation tools, with focus on the Functional Mock-up Interface (FMI) Standard. This approach eliminates the need of re-developing the same dynamic simulation model components to be used in different tools for power system analysis, thus reducing development time and required resources. In this paper, the model exchange procedure is discussed on the basis of a practical example, both from the model development (export) as well as the model usage (import) perspectives. Two commonly used simulation tools are used as demonstrative platforms. The simulation model is exchanged by using a Functional Mock-up Unit (FMU) file containing the model in a fully automated export-import process compliant with the Functional Mock-Up Interface (FMI) standard. A comparison between the simulation results produced by the two simulation tools is presented and discussed.

IEA TCP WIND Task 25 ”Design and Operation of Energy Systems with Large Amounts of Variable Generation” compiled Recommended Practices for power system impact studies, traditionally called wind and solar integration studies. This provides research institutes, consultants, and system operators with the best available information on how to model and study power and energy systems with large amounts of wind and solar energy. The Recommendations are presented as checklists that are also useful in benchmarking any integration studies: what has and has not been taken into account. The Recommended Practices contain the following sections: Input data; Scenario set up; Adequacy; Operational impacts; Dynamics; Analysing and presenting the results. Each section highlights the issues with the main recommendations, for small/medium wind and solar shares in the power system and also for wind and solar dominated systems. In this paper, Recommended Practices checklists are compared with modelling practises applied in a study of electrification of the transport and industry sectors in Sweden. Key challenges and trade-offs when performing studies of energy systems dominated by wind and solar power are presented together with suggestions on how the modelling community could facilitate the implementation of high quality studies of systems with high shares of wind and solar power.

The increasing integration of renewable energies into modern electricity grids is creating new challenges for grid operators and

energy traders. Wind and solar energy are highly dependent on the weather and are therefore particularly characterized by spa-

tial and temporal fluctuations. Therefore, precise and reliable power forecasts for hours and days into the future are essential

for grid stability, market optimization, and cost reduction. Moreover, the increasing availability and quality of power measure-

ments enables a variety of methods to adapt weather and power forecasts to these measurements, with combining these diverse

approaches often leading to improved accuracy. However,in an environment with changing conditions, such as additional con-

struction of wind turbines or different regularization of the grid operators, past behaviour can become outdated quickly, adaptive

combination offers the potential for further enhanced forecasting accuracy and reliability. Therefore, we present an adaptive

combination method that produces a combined forecast based on power forecasts of different weather models. Next to the usual

predictors, we use additionally spatio and temporal features. This approach is applied to different baseline and Machine Learning

models. We compare online machine learning methods such as Online Sequential Extreme Learning Machines (OsELMs) that

adaptively combine predictions with other benchmark approaches and individual forecasting models. One particular focus is on

the systematic analysis of defined update intervals (daily, weekly, monthly). During each interval, the adaptive learning process

accumulates new measurement and forecast data and adapts its weights automatically in order to optimize the prediction quality.

Both the combination and the adaptive training of the ML models show that the updates lead to improved forecasting accuracy.

The transport transition towards e-mobility requires distribution system operators to prepare in a timely manner, just like in case of the PV development. It seems appropriate the differentiate between home charging stations (wall boxes), which will be distributed over the whole grid, and fast charging stations (DC hubs), which require large power at certain points.

A first step in this direction is to estimate the current grid connection potential, i.e. the free connection capacities. A follow-up step with regard to home charging stations is the estimation of the grid expansion requirements on the basis of different scenarios for the market penetration of e-mobility. The comparison of the scenarios with the actual development subsequently represents the input variable for investment planning and management.

The basis for estimating the potential of fast-charging locations, which were carried out together with research institutions, were among other input parameters traffic analyses. It should be noted at this point that the actual locations and the speed of expansion of both home and fast charging stations are determined by our customers.

In order to ensure that investment planning is as targeted as possible the evaluation and modification intervals of these should therefore be increased at medium and low voltage level. This requires a high degree of automation of the grid analysis, especially at the low-voltage level. This goes hand in hand with corresponding data availability. This is also necessary in order to be able to process "e-mobility requests" as quickly as possible and in the best way.

An essential factor is the estimation of the simultaneity behavior of e-mobility. This is not to be considered on its own, but in combination with the existing load behavior. The estimation is regularly evaluated with grid-related measurement data and smart meter data and adjusted if necessary.

The results as well as the results of PV development, have been the basis for the adaptation of the grid planning guidelines. For example, the standard cross-sections for medium and low voltage as well as the rated power of the transformer stations have been increased. As a simple planning principle, the target value for the "characteristic short-circuit power" (loop impedance) at the low-voltage connection points in urban areas was increased to 1 MVA.

With the increasing market penetration of e-mobility, the expectation is that the share of public charging and thus the number of "charging hubs" will increase.

This paper addresses open-loop grid-forming (GFM) control of inverters, which enables fast dynamic response but poses challenges for current limitation during faults. Implementing virtual impedances in this context requires the time derivative of measured currents, amplifying noise. Conventional workarounds avoid ideal differentiation but perform poorly, especially under asymmetrical faults. To overcome these limitations, an observer-based approach is proposed that accurately estimates current derivatives without explicit differentiation. The method is evaluated through PSCAD time-domain simulations and frequency-domain analyses, comparing the behavior of different virtual impedance implementations and demonstrating improved fault performance for open-loop GFM control.

The increasing electrification of the transportation sector presents challenges for expanding charging infrastructure, particularly in urban areas like Berlin. The demand for charging stations competes with existing public road usage, and many businesses lack the resources to set up their own infrastructure. Multi-use concepts, which make private charging stations accessible to other user groups, help increasing infrastructure utilization and meeting charging demands. The Retail4Multi-Use project examines the potential of these concepts at retail locations in Berlin, analysing charging requirements for the years 2035 and 2045 in three scenarios: one without multi-use, one with its implementation, and one incorporating temporal flexibility of charging. The study models the electromobility ramp-up, generates synthetic driving profiles using mobility data, and calculates charging needs through dynamic simulations. The geographical distribution of demand is also assessed. Results show that, in 2035, approximately 3,300 charging points are needed at retail locations, rising to 7,400 by 2045. Multi-use concepts can increase energy usage per point by up to 255% by shifting demand from public spaces. Multi-use-concepts at retail sites with flexible charging times can reduce public infrastructure needs by up to 17%. These findings demonstrate the potential of multi-use concepts to optimize urban charging infrastructure use.

As inverter-based sources like Wind Turbine Generator (WTG) increasingly integrate into the power grid, concerns arise over

spinning reserves and frequency stability. The traditional Grid-Following (GFL) control approach does not adequately address

frequency deviations. In contrast, the Grid-Forming (GFM) method is a promising alternative that allows inverter-based resources

to directly control voltage and to provide system inertia. While GFM inverters can be effectively used with battery energy storage

systems, applying GFM to WTGs poses challenges due to constraints from the primary energy source. Sudden drops in the DC-

link voltage of Type 4 generators can also affect the mechanical components of the wind turbine. Control of the DC-link voltage

can be managed by either the machine-side converter or the grid-side converter. GFL units typically use the grid-side converter,

directly influencing active power feed-in, while GFM inverters affect feed-in power indirectly. This increases interaction between

the grid and WTG, impacting mechanical components. The simulation aims to systematically examine GFM and GFL WTG

facing angular jumps using DIgSILENT PowerFactory in the Electro-Magnetic-Transient (EMT) domain, focusing on GFM

while considering GFL as a reference

The electrification of heavy-duty vehicles demands very high charging capacities, which in turn require large-scale grid connections. Securing such connections, especially those above 10 MW, typically involves long planning and construction times, creating a major bottleneck for the rapid deployment of public truck charging infrastructure. To address this challenge, intermediate solutions are needed that can accelerate the rollout while ensuring reliable charging operations. One promising approach is the combination of smaller, more readily available grid connections with stationary battery storage systems. By temporarily compensating for insufficient grid capacity, these systems could provide high-power charging services until a full grid connection is established. This contribution examines the technical and operational conditions under which battery storage can effectively serve as a bridging technology for heavy-duty vehicle charging infrastructure. Particular attention is given to the interplay between grid availability, charging demand profiles, and storage system sizing, with the aim of identifying scenarios in which such hybrid solutions offer both economic and practical benefits for stakeholders.

In Germany and other European countries, a significant part of the verification and compliance procedure is based on detailed dynamic simulation Models implemented in a power system analysis software. There are requirements for plant and unit simulation models for the purpose of verification and conformity simulations based on the scope as either RMS or EMT model. In addition to the requirements for the models themselves, there are also plausibility and validation criteria to ensure model quality.

In Germany, these model requirements, including validation and plausibility scenarios, are specified in FGW Technical Guideline TR4 [1], which aligns with the procedures outlined in IEC 61400-27-2, but adds specific validation tolerance criteria.

With the increasing integration of offshore wind farms (AC or via HVDC systems), corresponding conformity studies are being carried out more and more frequently. However, there is a growing need to establish a standardized framework for simulation models and validation procedures for offshore connections. Since Rev. 9 of FGW-TR4, there has been a first chapter on the validation procedures based on VDE AR 4131 [2] for HVDC connection, which remains very generic – without a general model requirement scope and without plausibility tests.

In this context, particular attention is drawn to the offshore grid connection requirements of the TSOs Amprion and 50Hertz (ONAR), specifically it’s appendix detailing model requirements and validation criteria [3]. This appendix provides a more detailed and practical requirement list, which could serve as a solid foundation for future adaptations of the FGW standard.

This presentation provides an overview of the status of FGW-TR4 and ONAR Appendix Model requirement and outlines initial concept on how both could be harmonized in order to create an equivalent assessment basis for future conformity assessments based on the FGW's established assessment guidelines.

[1] https://shop.wind-fgw.de/produkt/tr-4-anforderungen-an-modellierung-und-validierung-von-simulationsmodellen-der-elektrischen-eigenschaften-von-erzeugungseinheiten-und-anlagen-speicher-sowie-deren-komponenten/

[2] https://www.vde-verlag.de/normen/0100511/vde-ar-n-4131-anwendungsregel-2019-03.html

[3] https://www.amprion.net/Dokumente/Strommarkt/Netzkunden/Netzanschlussregeln/Offshore/Annex-Simulation-Models-and-Studies.pdf

Vehicle-to-Grid (V2G) solutions are gradually being deployed, offering the potential to provide ancillary services, enhance grid stability, and generate revenue for Electric Vehicle (EV) owners. Aggregators play a central role by coordinating EV fleets to participate in electricity markets. However, their scheduling strategies often rely on aggregated fleet data. This approach can obscure behavioral diversity among individual users and lead to overestimation of fleet flexibility, especially in intraday electricity markets, where short-term availability is critical. To better understand these discrepancies, this study explores the potential of V2G systems to participate in intraday electricity markets through a detailed analysis of real-world residential EV operational data from Germany. Statistical methods are applied to assess the role of private EV fleets in short-term market environments by analyzing connection status, plug-in and plug-out patterns, and availability across different time scales. Key indicators, such as arrival and departure behaviors, connection windows, and fleet size, are analyzed to determine when EVs can provide flexibility to the grid. The results highlight significant differences between fleet averages and individual behaviors, emphasizing the importance of detailed statistical analysis for optimizing V2G market strategies and supporting the integration of EVs into electricity markets.

The connection network codes in Europe and more generally in the world are moving to require Grid Forming (GFM) capability from generation and storage devices. As GFM control will help stabilise the grid, it might create additional flows and stress in the battery and inverter. To evaluate the change in behaviour on the device and to provide both qualitative and quantitative insight on the expected solicitation, this paper will simulate the response to different events for three types of Energy Storage Module (ESM) installation:

• Grid Following Energy Storage Module providing Frequency Containment Reserve

• Grid Forming Energy Storage Module at constant power

• Grid Forming Energy Storage Module providing Frequency Containment Reserve

The models used in this study are fitted to match the expected requirements for GFM ESM in France, which are based on the draft version of Requirement for Generators V2 from ACER and the latest version of Technical Report on GFM technologies from ENTSO-E. The main impacting requirement is that as of today’s knowledge, France will ask for GFM only within storage and inverter capability, therefore, no additional storage nor oversizing of hardware is requested from a GFM than from a Grid Following (GFL) unit.

These models have been tested against actual voltage and frequency measurements from Phasor Measurement Unit acquired during different grid transients over 15 minutes periods. The impact of GFM requirement parameters, such as equivalent inertia or effective impedance, is also evaluated on the same test cases. Results illustrate that GFM controls only creates minor deviation of the power from its setpoint, with a standard deviation of less that 0.2% with the worst case of parameters.These variations have no significant effect on the ESM’s state of charge and are minimal compared to the stress induced by participation in Frequency Containment Reserve (FCR).

Additional simulations have been performed to showcase that even if the control impact on power in normal situation is very low; in case of more severe system events such as phase shift, the GFL and GFM act in a very different way. In such situations, the GFM contribution exceeds that of the GFL mode, but remains limited in duration.

Grid-forming (GFM) control is a critical function for grid-connected inverters, especially as the penetration of inverter-based resources (IBRs) continues to rise. A common implementation of GFM control employs a cascaded voltage and current control structure (dual-loop), where the voltage regulator generates a current reference for the inner current loop. Such control schemes are found in various applications, including HVDC and FACTS systems, depending on converter topology and grid code requirements. However, the dynamic interactions between the voltage and current loops in dual-loop GFM control remain insufficiently explored in the literature.

This paper presents a detailed modeling and analysis of the interactions between the voltage and current loops in dual-loop GFM control, with a focus on transient grid conditions such as voltage ride-through and phase jump events. First, various dual-loop control strategies are reviewed, and their dynamic behaviors during grid disturbances are examined using a phasor-based analysis to highlight loop interactions and their effects on grid support and fault ride-through performance. Next, analytical models in the form of transfer functions are developed and validated through numerical simulations. These models are used to compare different dual-loop designs and provide deeper insights into the control dynamics observed in the phasor-based analysis. Finally, based on the developed models, design guidelines and parameter tuning strategies are proposed and validated to enhance GFM performance under grid transients.

This study investigates how smart charging and vehicle-to-grid (V2G) technologies affect the European energy system in the 2050 under climate target constraints. Using an energy system model that explicitly represents EV batteries, charging infrastructure, and investment costs, we analyse passenger EVs within a broader context including power, heat, and industry sectors. The results show that coordinated charging is essential to limit infrastructure deployment, while V1G and V2G utilisation strongly depend on grid development. V1G provides the largest cost savings, with grid expansion and smart charging offering additive benefits. V2G adoption is highly context-specific: infrastructure costs influence both its utilisation and market value, and the additional charging required is limited to 14\%, supporting widespread adoption without overloading batteries. V2G contributes to winter peak supply in countries with seasonal gaps and stores excess PV generation during summer. Neglecting infrastructure costs can distort charging schedules and market signals. Overall, the study highlights the importance of coordinated charging and realistic infrastructure modelling to unlock EV flexibility and support system decarbonisation.

Despite a global shift toward requiring Grid-Forming (GFM) capability for Power Electronics Interfaced Resources, there is still no consensus on how to verify GFM behavior during the network connection process. The response of GFM units, as implemented in the context of Power Park Modules (PPMs) including Electricity Storage Module (ESM), depends on several factors, such as the type of network disturbance (e.g., RoCoF events, voltage phase angle jumps, voltage magnitude changes), the tuning of GFM control parameters, and the physical network impedances. As a result, classical time-domain performance metrics—such as settling time, damping ratio, and rise time among others - can significantly vary depending on the specific test scenario. This variability highlights the need for refined test-specific performance requirements. One promising approach to tackle this issue is the use of envelope-based criteria to define GFM compliance criteria tailored to each test configuration. This work introduces envelope-based criteria to define GFM requirements which are aligned with the latest ENTSO-E recommendations for Power Park Modules. These envelopes are based on the expected ideal behaviour of GFM inverters and cover the minimum requirement expected from ENTSO-E, while incorporating margins around the ideal response to accommodate variations in implementation across different manufacturers. In order to validate their relevance, a generic open-source RMS model is used with different parameters and control structures. The different choices done into the implementation of the model will be detailed alongside their impact on the installation’s dynamic behavior. This model was previously compared to an equivalent EMT model to assess its representativeness and both models are used to show their ability to meet the envelope-based pass/fail criteria. The validation of the proposed envelope criteria is based on a set of various test scenarios. These tests notably include: (1) voltage phase angle jump, (2) voltage magnitude jump, (3) response to Rate of Change of Frequency (RoCoF) events, and (4) response to variation on the grid topology (Short Circuit Ratio step). The contributions of this paper are thus twofold: introducing the use of envelope-based criteria for GFM compliance criteria and validating their relevance by simulations with an open-source RMS model.

The rapidly expanding market for green hydrogen and its derivatives faces significant uncertainties that challenge its potential trajectory. Recent research indicates that the European Union's REPowerEU initiative targets to import 6 Mt of hydrogen by pipeline and 4 Mt of ammonia by 2030, might be overly optimistic. In this context, Morocco emerges as an important player due to its proximity to Europe, robust renewable energy potential and supportive policy strategies. In this paper we assess the impact of three sub-sectoral demand scenarios for 2035 and 2050 describing different value chain shifts and strategic drivers utilizing a sector-coupled energy model.

Given the importance of renewable potential for the results, the robustness of all scenarios is furthermore tested against ten historical weather years. Our findings reveal that the optimal capacity expansions of wind, solar and electrolyzers for the Moroccan energy system vary significantly among the different demand scenarios and that they are sensitive to weather conditions and interest rates. Strategies for long-term investment decisions depend highly on derisking financial instruments to guarantee off-takers a resilient landscape.

We contextualize the required expansion pathways for green hydrogen, ammonia, methanol, and green steel in alignment with Morocco's export strategy, highlighting the competitiveness of these products based on marginal production costs. Additionally, we discuss the co-benefits of climate change mitigation alongside various export scenarios. These scenario-based findings can inform policymakers about the energy system pathways of Morocco and its prospective role in developing the hydrogen market within the MENA region. It is projected that Morocco could contribute up to 20% of the global hydrogen market by the year 2050.

A paradigm shift from Grid Following (GFL) to Grid Forming (GFM) converter control has been proposed by some transmission system operators (TSO) to address challenges around fast inertial response, not least during severe contingencies, and other stability problems that are observed in power systems with few remaining synchronous generators and large long-distance power flows. In Europe, requirements for GFM controls for Power Plant Modules (PPMs) are under consideration for upcoming European regulations (RfG 2.0, NC HVDC 2.0) and have been included as additional requirements in the German grid code for HVDC-connected PPMs, and as an optional service in the UK grid code.

Compared to GFL controls, GFM converter controls deviate more from a converter’s power setpoint , due to the dynamic reaction of the controls to, e.g. voltage phase jumps, frequency gradients and voltage events. In wind turbine generators (WTG), this introduces a stronger coupling between grid events and the mechanical system, which had previously been overcome in full-converter turbines. Implementation of GFM on WTGs therefore faces several obstacles that make the application of this control concept challenging:

- WTG converters are not designed with electrical energy storage and must satisfy active power requests by corresponding active power changes on the machine-side converter, and therefor onto the mechanical WTG components

- The only inherent energy storage of a WTG is the energy stored in its rotating masses.

- Access to this energy is limited by the dynamic limitations of WTG’s, e.g. on the rotor speed, as well as load limitations of drivetrain, bearings, and other mechanical structures.

A concept study is presented in this paper showing how GFM controls may be implemented on a WTG PPM while respecting the above limitations and also providing key GFM control functions, including the following:

- Instantaneous reserve / inertia power provision.

- Dynamic voltage control without reactive current specification / fast reactive power response.

- Temporary islanding of a High-Voltage Direct Current (HVDC)-connected PPM in case of blocking of the HVDC converter.

Electro-magnetic transient simulation results and full-scale converter test rig results are provided to illustrate the concept study.

For power generating technologies such as wind and PV so-called grid codes have been providing the technical framework for their grid connection for the last 25 years. These grid codes impose important requirements on the electrical characteristics of these installations in order to ensure as reliable and secure operation of the power system as these new generation technologies take over the dominant role of power supply and, hence, of ancillary services to the power system.

The growing fleets of electric vehicles (EV) with still rising load capacities up to several 100 kW and now coming up bi-directional coupling to the power grid requires also to integrate these prosumers into the scope of respective connection codes. Hence, in the previous years, some European countries have already published initial requirements on the grid connection capabilities of EVs and respective charging systems.

Accordingly, the European Network Codes, initially published in 2016 without having EVs in their scope, will also address respective grid code requirements for EVs and charging installations within the next revision expected in 2025.

After an introduction to the basic objectives and scope of grid codes and, in particular, the European Network Codes, the presentation provides an overview on the new requirements for EVs and charging systems as announced in the revised European Network Codes. The requirements will be distinguished between uni- and bi-directional couplings and also between the three capacity-based types of bi-directional EVs defined by the Network Codes. The paper will also provide an introduction to respective compliance schemes as stipulated in the Network Codes.

This paper investigates the impact of inertia provision on the operation of residential battery storage systems (BESS). An optimisation model aimed at self-consumption optimisation (SCO) is expanded to include power and energy reservation for inertia. Simulations are carried out for various amounts of allocated power and energy for inertia, as well as for different household configurations. The analysis considers techno-economic key figures for households, as well as the general behaviour of the BESS (i.e. examining power flows and state of charge).

The results indicate that allocating power and energy for inertia provision with up to 40% of the rated power has a negligible impact on operation for households without an electric vehicle, since the BESS's charging and discharging processes can be shifted within the photovoltaic production and load times. However, in households with electric vehicles, reductions in the self-consumption quota can already be seen even with smaller inertia ratios, as the high negative residual loads can be covered even less by the BESS due to the reserved power bands. Nevertheless, it can be concluded that providing inertia with less than half of the nominal power has a minor effect on the prosumer's revenue after SCO in most household configurations.

In this paper, an analytical model of a five-degree-of-freedom wind turbine is derived, showing the effects of grid-forming control of the grid side inverter on the mechanical loading of the wind turbine system. Therefore, a nonlinear state space representation of the grid-forming inverter toward the point of common coupling (PCC) is derived and reduced to a more tractable model. The wind turbines are connected to the inverter via the DC link voltage. The paper shows how appropriate DC voltage control can be used to ensure a rapid response to disturbances caused by the grid-forming behavior of the grid-side inverter. The design approach is tested under various grid events, such as angle jumps due to changes in electrical load and power fluctuations in the lower subsynchronous frequency range, to demonstrate the effect and performance of the control concept on the turbine load.

Active power-controlled photovoltaic (PV) energy sources are equipped with control schemes to regulate the active power fed into the grid (real power) even below the maximum power point. In [1], two methods — a model-free and a model-based algorithm — were presented to investigate how quickly PV systems can adjust their power to provide negative and positive inertia. Furthermore, for the orchestrated frequency and voltage stabilization of distributed energy resources (DERs), a general concept of dynamic virtual power plants (DVPP) was presented in [2]. DVPPs explicitly incorporate dynamic aspects at all levels for controller design and grid-integrated operation. The basic idea is that the DVPP, as a whole, participates in the ancillary network services and interacts dynamically with neighboring network elements. For this purpose, the desired dynamic global behavior of the DVPP in a network section is described by an aggregated transfer function. To distribute the tasks to the individual generator units of a virtual power plant, these are divided (disaggregated) into local reference models, which are used for a model reference controller design [3].

So far, the concept has only been investigated for large distribution grids with few concentrated and symmetrical loads. In this work, a DVPP for active distribution grids with asymmetric loads and distributed PV generation units without storage is investigated using the 13-node test feeder grid topology, which provides a suitable benchmark for the DVPP system in active distribution grids for unbalanced systems. The 13-node test feeder is characterized by being short, relatively highly loaded, and single voltage regulator at the substation, overhead and underground lines, shunt capacitors, an in-line transformer, and unbalanced loading [4].

For the investigations presented here, the original 13-node test feeder system is expanded to include active power-regulated photovoltaic energy sources and an external grid, with power balance-dependent network frequency calculated using an aggregated swing equation that takes into account power imbalance at the point of coupling between the distribution and external grids. The design process of the global DVPP, the local control of the PV systems, and the results for various load scenarios are presented and discussed.

[1] Schulte, Horst: Advanced Control of Grid-Integrated Renewable Energy Power Plants, John Wiley \& Sons 2024 (IEEE Press Series), doi: 10.1002/9781119701415

[2] Marinescu, Bogdan.; Gomis-Bellmunt, Oriol.; Dörfler, Florian.; Schulte, Horst; Sigrist, Lukas: Dynamic Virtual Power Plant: A New Concept for Grid Integration of Renewable Energy Sources. In: IEEE Access, 2022, doi: 10.1109/ACCESS.2022.3205731

[3] Schulte, Horst: Takagi-Sugeno Model Reference Control of Photovoltaic Power Plants to Provide Instantaneous Reserve. In: Proceedings of IEEE International Conference on Fuzzy Systems 2025 (FUZZ-IEEE). IEEE. Reims, France, June 06-09.07.2025.

[4] 13-Node test feeder was created in 1992 and approved by the DSA Subcommittee during the 2000 PES Summer Meeting.

https://cmte.ieee.org/pes-testfeeders/resources/

Achieving net zero requires green hydrogen produced from renewable energy sources to decarbonize existing hydrogen applications and hard-to-electrify sectors such as steelmaking. Projections suggest a sixfold increase in global hydrogen demand by 2050. According to recent analysis by McKinsey and the Hydrogen Council, around 40 million tonnes per annum (mtpa) of hydrogen-equivalent fuels could be transported globally by 2035. The EU hydrogen strategy sets a target to import 10 mtpa of renewable hydrogen by 2030. To assess Europe’s medium-term import potential, this study estimates supply cost curves for green ammonia — a key hydrogen derivative — at various EU ports by applying a high-resolution PtX market model chain and considering a ramp-up based on announced and planned capacities across Africa and South America.

The study will utilise a first version of a Global PtX market model consisting of modules for 1) the GIS-based identification of suitable areas and the simulation of renewable profiles for those sites, 2) the cost-optimisation of specific Power-to-X commodities using PyPSA, 3) the identification of transport routes and calculation of transport costs 4) the projection of local demands and 5) the market model which simulations the supply and demand situation at export ports and estimates the supply cost curve and import ports.

The geographical scope are around 300 sites in countries from South America and Africa with strategies and project plans in place. Landlocked countries are excluded. The analysis is conducted for 2035. According to the IEA hydrogen production project database, 70% of the countries' announced projects plan to produce ammonia. Furthermore, the H2Global auction for ammonia led to a successful contract, underlining the relevance of green ammonia. Therefore, the analysis focuses on the market situation and supply cost curve estimation of green ammonia and ammonia for hydrogen end-use. The transport costs are considered using a detailed assessment of transport routes and shipping cost calculation.

Country-specific cost of capital scenarios for the projects are taken from a detailed calculation published recently in a Nature journal paper. The paper provides cost of capital rates for a public de-risking and a private commercial scenario. The GIS-based analysis of the most suitable areas dedicated to PtX export capacities uses more than 30 criteria. Regions suitable and needed for producing hydrogen for projected local use for green fertiliser or steel production, or for supplying haul aviation and shipping with renewable Power-to-X fuels will be excluded for the purpose of exporting hydrogen. Production volumes per country are defined based on announced projects, leading to a global supply curve before trade. Detailed transport cost modelling is used to derive port-specific delivered supply curves.

The quantified, temporally resolved supply curves at European ports of this study can be used as an input for further detailed analysis down the supply chain. Furthermore, the results can be used to analyse the competition among different hydrogen supply routes (import vs. production in Europe) and their respective infrastructure needs for the European energy system.

Motivated by the need to mitigate climate change, reduce urban air pollution, and curb reliance on volatile fuel prices, this study investigates the integration of solar photovoltaic (PV) systems into electric bus (E-bus) charging infrastructure, for the proposed Bus Rapid Transit (BRT) Line N1, in the Maputo Metropolitan Area (MMA). The urban mobility pattern in Maputo is characterized by strong unidirectional flows and peak-hour demand, with inbound trips in the morning and outbound trips in the late afternoon. Accordingly, the operational schedule was defined within peak periods, with three round trips per bus adopted for simulation. The E-bus load profile was defined using a physical model, yielding an average specific energy consumption of 1.91 kWh/km. A solar resource assessment based on PVGIS-SARA2 data indicates an annual daily average global horizontal irradiation (GHI) of 5.2 kWh/m², peaking at 6.4 kWh/m² in February and dropping to 3.7 kWh/m² in June. The PV charging station was sized to meet daily demand and modelled as a grid-connected, zero-export, strict self-consumption system. Results demonstrate both the technical feasibility and scalability of this approach, providing strategies to manage simultaneous peaks in transport and energy demand, thereby contributing to sustainable urban mobility and supporting the energy transition.

The introduction of Renewable Energy Sources (RESs) to electrical power grids creates concerns over grid power imbalances. Most RESs are non-dispatchable, meaning that natural elements have a significant impact on how much power can be produced, which leads to issues with frequency stability, maintaining grid energy balance and supporting overall fault levels. It also leads to issues with reactive power provision, often needing compensation to maintain voltage levels, and can influence short circuit fault currents when connected at the distribution level. Therefore, RES poses operational challenges and thus the interest in using electrochemical battery storage systems to provide bi-directional power flow to maintain AC power grid transient frequency stability (TESS) and support more sustained energy delivery (BESS). The voltage level constraints of commercial DC-DC and voltage source converter (VSC) power electronic devices is limited to around 800V operational (1200V IGBT devices). Although higher voltage power electronic devices and VSC structures are being developed, to-date, the 1200V IGBT is the industrial benchmark device. This results in the 3-phase AC connection of the battery storage system via a VSC of around 690 Vrms in practice. Thus, an interface transformer is necessary in the TESS or BESS system to connect to higher voltage, 3-phase electrical networks. This paper presents a sizing study for the static transformer in either a TESS or BESS system, as rated for operation and lifetime longevity. The static transformer is then compared with a rotary transformer system comprised of a low voltage induction machine mechanically integrated with a high voltage, low per unit inductance synchronous machine that electrically connects to the utility power grid. While providing the necessary voltage conversion from the switched DC system, and the energy transfer, the rotary transformer component also provides transient fault current to the grid during grid disturbances.

Selected references

S. Ehsan, R. Ehsan, and R. Mohammad et. al.: “Impact of distributed generation on protection and voltage regulation of distribution systems: A review”, Renewable and Sustainable Energy Reviews, vol. 105, pp 157-167, 2019.

C. M. Affonso, M. Kezunovic, “Technical and Economic Impact of PV-BESS Charging Station on Transformer Life: A Case Study”, IEEE Trans. On Smart Grid, Vol. 10, No. 4, 2019.

A. Azmi, J. Jasni and N. Azis, et. al.: “Evolution of transformer health index in the form of mathematical equation”, Renewable and Sustainable Energy Reviews, 76, pp.687–700, 2017.

N. Etherden, M. Bollen, “Dimensioning of Energy Storage for Increased Integration of Wind Power”, IEEE Trans. on Sustainable Energy, vol. 4, iss. 3, pp. 546 – 553, 2013.

Y. Hu, et. al.: “Investigation of Transient Energy Storage Sources for Support of Future Electrical Power Systems”, IET Renewable Power Generation, Early Access, 2020.

Recent Iberian Peninsula blackout indicates the stability concerns of interarea oscillations, which happened a few minutes before the blackout event. Power system stabilizers (PSS) have been conventionally providing oscillation damping services to power systems by modulating the field voltage of a synchronous generator (SG) through normal automatic voltage regulator (AVR) control. It utilizes the machine’s power couplings to damp low frequency oscillation in multi-area power systems; hence, the proper turning of PSS requires complicated state-space modal analysis which involves high-order of SG models.

Power system low frequency oscillations have been proven as a small-signal stability property. Modulating system active power flow can be very efficient in damping such oscillations. Previous PHIL (Power-hardware-in-the-loop) demonstration by NREL showed a 10MW battery inverter that can effectively stabilize a GW-scale interarea system by injecting active power compensation off-phase to system frequency oscillations. This gives the opportunities for SG-based power plants to perform more efficient PSS functions using active power modulation given sufficient control bandwidth of SG’s governor.

This paper presents the PHIL demonstration of how a SG-based power plant (Synchronous Wind power plant) can provide low frequency oscillation damping, using active power and reactive power modulations. A synchronous wind turbine is a variable-speed wind turbine interfacing with the grid through a fixed-speed SG using a hydraulic torque converter. Therefore, their operation and consequent grid impacts are similar to conventional machine-based power plants. The PHIL show a SG-based plant can provide efficient damping for interarea oscillations, without using curtailment (for wind power plant); however, it triggers machine natural oscillation mode when the reference of damping torque reaches its upper or lower limit. The results can bring further insights to how a group of small SGs with fast power control bandwidth can contribute to interarea oscillation damping and enhance power system small-signal stability.

Introduction

Energy system models have been widely used to foresee medium- and long-term energy transitions. However, most energy system models generally have rough time slices, such as 12 or 16 slices per year. The problem with this rough time slice is that it does not adequately reproduce the short-term flexibility among the flexibility required in response to variable renewable energy penetration. Rough time slices in energy system models are particularly challenging in terms of computing power when modelling the transmission substation units used in energy system modelling studies, which can be classified into more than 350 regions and reflect transmission capacities.

Methodologies

To address these challenges, a new modelling method is proposed that introduces high-resolution analysis for critical periods and processes other periods at a coarse time slice. The steps of the method are as follows:

Definition of critical time slices:

A specific period of time (e.g. the first week of July) with high demand and high fluctuations in renewable energy output is selected and this is modelled at hourly resolution (e.g. 168 slices per week).

The remaining annual periods are aggregated into 16 coarse slices to ensure computational efficiency.

creation of realistic curves:

For the key periods defined, demand curves and solar and wind supply curves are created on an hourly basis to reflect realistic variations.

For other periods, aggregated information based on seasonal and day/night data is used.

incorporation of existing capacity:

Capture the capacity calculated in the previous model run in year t-1 and treat this as the “existing” capacity for year t.

model run for year t:

Provides existing capacity for year t and optimises the additional capacity needed to manage supply and demand variations through high resolution slices and coarse slices in critical periods.

Major Findings

System stress testing: identify periods of extreme stress and assess the suitability of existing and proposed capacity mixes.

Flexibility analysis: assesses the role of storage, demand response and grid coordination to mitigate variability.

Incremental capacity planning: provides actionable insights on annual incremental investments rather than major system modifications.

This hybrid approach bridges the gap between computational feasibility and the need for realistic high-resolution system modelling. By exposing hourly variations during critical periods, it enables the energy system capacity mix to meet real-world challenges and supports a more resilient and cost-effective energy transition.

-objective/context:

The increasing share of renewable energy sources (RES) and their inverter-based resources (IBRs) bring, along with net-zero benefits, new challenges regarding interoperability. The necessity of having more IBRs will require multiple players to operate within a context of intellectual property (IP) protection, which cannot impede the need for a system that functions correctly. One potential technique used to assist the detailed studies through electromagnetic transients (EMT) simulations is the conversion of the principal original equipment manufacturers (OEM) into shareable black-box versions through dynamic link libraries (DLL), which will prevent IP violations while preserving simulation accuracy by including the original elements within the DLL. In particular, this work focuses on increasing simulation fidelity by transposing full-switching models of offshore wind turbines (OWTs) and provides valuable recommendations.

-methods:

The chosen approach initially involves translating the model one-to-one into Simulink, enabling the generation of an equivalent C-code version of the overall behavior that can be converted into a PSCAD module via the IEEE Cigre Wrapper. More specifically, it translates PSCAD’s interpolation feature into Simulink modules to create a DLL compatible with PSCAD’s interpolation devices, such as the IGBTs. Finally, potential strategies to enhance the speed of the equivalent DLL were identified, along with consideration of additional aspects, such as simulation setups, that might impact the accuracy of the full-switching equivalent DLL.

-outcomes/conclusion:

The outcomes include the complete full switching DLL of the OWT, along with the relevant guidelines for performing the conversion and validating a component whose inaccuracies can easily lead to misalignments in the IGBTs, thereby impacting overall converter operation. Additionally, a study will be conducted to determine whether the full switching of DLL elements can be compatible with both 50/60Hz systems in order to assess potential impacts on the harmonic models.

As extreme weather events become more frequent and severe, planners need tools to evaluate how the grid performs under credible worst-case scenarios. This report introduces a stress testing framework that complements traditional resource adequacy analysis by simulating high-impact, low-probability (HILP) events—such as prolonged cold snaps, heatwaves, and renewable droughts—while focusing on the role of interregional transmission in mitigating risk.

The method involves four steps: defining extreme event scenarios, identifying key risk drivers, applying stress variables (e.g., thermal outages, renewable variability, load uncertainty, and transmission constraints), and conducting multi-day simulations. By using weather-correlated, synchronized data across neighboring regions, the approach better represents how transmission and external support influence system resilience.

A case study in the Southwest Power Pool (SPP) applies this framework across several types of extreme events and evaluates different assumptions about neighboring systems and import capabilities.

Key findings include:

• Interregional transmission significantly enhances resilience, providing a critical buffer during times of internal system stress. Even when neighboring regions are also under duress, coordinated imports help avoid outages.
• Stress testing enables detailed examination of outlier events that traditional probabilistic methods often mask, while avoiding the need to assign precise probabilities to rare but consequential conditions.
• By resampling historical data to create alternative renewable profiles and thermal outage conditions, stress testing expands the range of credible risk scenarios and benefits from growing access to high-quality weather-correlated datasets.

This approach offers planners a more realistic basis for evaluating extreme system risks and supports more robust, transmission-aware investment decisions.

As energy systems continue to evolve, ensuring compliance with grid code standards is crucial for maintaining system stability and interoperability. This presentation explores the certification process of grid code requirements using Hardware-in-the-Loop (HIL) testing methodologies. We begin by defining HIL and its role in simulating real-world conditions for electrical components and systems. Recent updates to grid code standards, such as EN 50549-10, are discussed, focusing on their guidance for using HIL in conformity evaluation. The presentation outlines a proposed certification process that incorporates HIL, discussing its potential benefits in terms of efficiency and effectiveness for certifying product platforms. Attendees will gain an understanding of how HIL can be applied in certification processes to support compliance with modern grid requirements.

The rapid growth of large-scale wind power plants (WPPs) and other inverter-based resources (IBRs) is significantly transforming and impacting power system design and operation, introducing new complexities and challenges. In this evolving landscape, the demand for sophisticated Electromagnetic Transient (EMT) models to ensure seamless integration and reliable operation of these devices is increasing.

Validation of EMT models is essential for ensuring they replicate the electrical characteristics of WPPs in the time domain with high accuracy, thereby providing confidence in their predictive capabilities and operational reliability. These models are quality-assured by validating against measurements from a prototype turbine or test rigs, specifically for fault ride-through (FRT) cases.

Currently, the state-of-the-art in validation techniques (IEC 61400-21-2) includes Full System Validation and Play Back Validation approaches. Full System Validation involves modeling the system, including the most relevant equipment, and simplifying the remaining parts. Play Back Validation, on the other hand, involves using recorded data from the actual system to test the model’s accuracy in replicating the real system behavior under specific events or conditions. Both approaches have their merits and are crucial for establishing the credibility of EMT models.

These validation methods, with their advantages and disadvantages, are well-established for grid-following (GFL) models. However, validation of grid-forming (GFM) technology, critical to enhancing grid stability and resilience of future power systems, may pose some unforeseen challenges as the existing methods may not fully capture its emerging functionalities. Some capabilities specific to grid forming may be challenging to test for the first time on equipment/plants connected directly to the power system. This gap highlights the need for developing tailored validation techniques that can address the unique characteristics of GFM models.

This paper will offer a state-of-the-art review of existing requirements for GFM model validation and explore ongoing discussions in various forums. By examining current requirements, standards and practices, the research seeks to identify established protocols for GFM validation and highlight emerging trends and considerations being debated in the field. This investigation will provide insights from an Original Equipment Manufacturer (OEM) perspective, aiming to ensure that GFM models can be reliably used in the design and operation of future power systems. Through rigorous validation, confidence in GFM models can be enhanced, facilitating their integration into modern grids and supporting the transition to sustainable energy systems

In the Nordic countries, seasonal variations limit the use of solar energy due to a mismatch between energy supply and demand. As the expansion of solar technology installation, especially photovoltaic (PV), evaluating multiple solar energy production systems in combination with storage systems, including both heat and electricity demand, is of particular interest for large industry and business parks.

This study aims to assess the matching of solar energy supply with the local community's power and heat demands of a business park consisting of warehouses. Various installation coverage of rooftop PV panels and solar thermal (ST) systems, combined with thermal energy storage (TES) of different sizes, have been evaluated. The input data includes roof area, solar irradiation, PV power production from an existing system, electricity (annual amount 1.41 GWh), and heat (annual amount 6.58 GWh) demand profiles, as well as district heating distribution and ambient temperatures. Key technical parameters analyzed are the self-consumption (SC) and self-sufficiency (SS) ratios, evaluated for electricity, heat, as well as the overall energy system (i.e., the combined electricity and heat).

Additionally, excess and imported electricity, energy balance, and waste heat are estimated. The results show that a significant portion of the produced heat is wasted, while surplus PV electricity can be exported to the grid, generating some economic value. The currently assumed TES capacity (70 MWh) is insufficient to store the total excess heat, leading to poor SC and SS ratios. Overall, the TES required to reach high self-sufficiency should be large in size, which in fact is infeasible, while smaller storage does not make a noticeable impact. Moreover, achieving a zero-waste heat and a complete heat SC scenario with a 70 MWh TES capacity would require allocating 7% installation coverage of the roof area to ST (equivalent to 1.2 MW). Concurrently, the PV system will cover 48% installation coverage of the roof area due to the power point of connection limit (equivalent to 1.4 MW). Therefore, leaving unutilized area could be an advantageous solution for the future, when TES or the power point of connection capacity is expanded or excess thermal energy is utilized.

Future research could focus on a techno-economic assessment to determine the optimal system size by balancing economic and technical metrics, potentially including other energy storage or boiler technologies.

The electrification of commercial vehicle fleets presents a critical opportunity for decarbonizing urban logistics. However, it introduces complex challenges, particularly in balancing infrastructure investments, energy system integration, and operational cost control. This study addresses these challenges by developing a strategic decision-support model aimed at optimizing long-term infrastructure planning for electric delivery fleets. Special emphasis is placed on the role of bidirectional charging and the integration of local renewable energy sources such as photovoltaic (PV) systems.

The core of the work is a mathematical optimization model formulated as a Mixed-Integer Linear Programming (MILP) problem. It evaluates infrastructure and operational configurations based on real-world input data, including dynamic electricity tariffs, high-resolution hourly PV generation profiles, vehicle energy consumption, and operational schedules from an ongoing electrification project in Switzerland. The case study involves a parcel logistics company aiming to fully electrify its delivery fleet across 12 national hubs by 2035. The analysed site, a former freight yard now undergoing redevelopment, provides a unique opportunity to explore infrastructure decisions within a constrained urban context.

The model minimizes the Total Cost of Ownership by applying two complementary analyses to each scenario: a conventional assessment of infrastructure and vehicle investment costs, and a dynamic evaluation that captures time-dependent operational parameters. These include vehicle usage and charging schedules, photovoltaic generation patterns, and temporal variations in electricity prices. The model simultaneously optimizes the sizing of key infrastructure elements, such as photovoltaic systems, stationary battery storage, vehicle batteries, and the grid connection, while accounting for realistic technical and temporal constraints. In addition, it determines cost-efficient charging and discharging strategies, incorporating bidirectional energy flows and dynamic tariff structures. Embedded in a scenario-based framework, the model enables systematic exploration of infrastructure configurations to identify cost-effective solutions and enhance overall system resilience.

Key findings show that temporal alignment between PV production and fleet availability significantly affects cost outcomes. Bidirectional charging proves especially beneficial for maximizing self-consumption of PV electricity and reducing dependency on expensive grid imports during peak hours. Seasonal planning and the strategic sizing of battery storage also play crucial roles in minimizing operational expenses. The results provide actionable insights for logistics operators, energy planners, and policymakers aiming to design cost-effective, resilient, and scalable fleet electrification strategies.

The research is based entirely on original modelling and analysis, supported by field data collected in collaboration with project partners, including a logistics provider, energy supplier, and charging infrastructure manufacturer. It is part of an applied research project and is situated within the context of a larger academic and industrial collaboration.

As fleet electrification accelerates, the need for reliable and cost-efficient charging infrastructure becomes increasingly crucial. Sharing corporate chargers with third parties creates strategic collaboration opportunities for fleet operators, charge point operators, and depot managers. It offers financial and ecological advantages by increasing the utilisation and efficiency of existing assets. However, shared use introduces operational challenges - such as coordinating with host depots, scheduling sessions, and resolving conflicts - which makes effective demand and capacity management essential.

The FAMOUS project enables companies to offer their charging infrastructure to authorised external users via an innovative digital platform. By intelligently matching charging demand with available capacity, the platform facilitates coordinated access through a smart booking system, unlocking previously unused potential. Additionally, it supports grid integration by providing local grid operator with estimated data on power consumption.

This contribution examines the technical and operational challenges of deploying a booking system that incorporates calendar-based reservation management. Using a multi-stakeholder approach, it critically evaluates the advantages and limitations of a centralised reservation architecture and identifies key development requirements for integrating reservation functionalities into existing EV infrastructure operations.

The energy transition requires flexible technologies

to maintain grid stability, and electrolyzers are playing an

increasingly important role in meeting this need. While previous

studies often question the dynamic capabilities of large-scale

alkaline electrolyzer systems, we assess their potential to provide

balancing services using real manufacturer data. Unlike common

approaches, we propose the decoupling between the total electrolyzer

power and a smaller fractions of power actually offered

on balancing markets. Adapting an existing methodology, we

analyze alkaline electrolyzer systems and extend the assessment

to Germany and Europe. Our results show that large-scale

electrolyzers are technically capable of delivering fast-response

balancing services, with significantly lower dynamic requirements

than previously assumed. The planned electrolyzers in Germany

could cover the entire balancing capacity market, potentially

saving around 13 % of their electricity costs, excluding energy

balancing revenues. The decoupling also resolves part of the

trade-off for electrolyzer manufacturers, enabling the design of

less dynamic but more stable systems.

Achieving the European Green Deal’s goals requires deep decarbonization of buildings and transport, which are major sources of emissions. Heat pumps (HPs) and electric vehicles (EVs) support this shift through high efficiency and renewable integration. In cold-climate regions like Dresden, where heating demand is high, air-source heat pumps (ASHPs) coupled with photovoltaic (PV) generation and bidirectional EVs offer a promising solution. PV-coupled ASHPs reduce grid reliance by utilizing on-site solar energy, while Vehicle-to-Home (V2H) EVs provide flexibility during peak periods. Yet without coordination, their operation may intensify demand spikes rather than reduce them, highlighting the need for intelligent scheduling to fully harness the potential of distributed low-carbon technologies. Coordinating residential energy systems requires balancing competing objectives with differing priorities. Traditional approaches often rely on predefined weights, which can be difficult to select and may lack flexibility. To address this, this study adopts the Non-dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm that generates a Pareto front: a set of non-dominated solutions representing different trade-offs. This enables flexible decision-making based on user preferences or policy goals. The NSGA-II optimization targets three key objectives: (1) minimizing electricity costs under time-of-use pricing, (2) reducing CO₂ emissions based on time-varying emission factors, and (3) smoothing net-load profiles to reduce grid stress. These goals often diverge; for instance, the cheapest electricity may coincide with high-emission or peak-load periods. Simulations are conducted over daily cycles using real residential load and PV generation data from Dresden. Results are compared against heuristic control strategies to assess the added value of coordinated scheduling. Simulation outcomes are evaluated across different household usage scenarios to reflect behavioral and demand variability. Findings show that coordinated EV discharging significantly improves cost-efficiency and emissions performance, particularly under high-demand conditions such as winter evenings. The NSGA-II algorithm reveals clear trade-offs between conflicting goals and generates a Pareto front of optimal solutions tailored to user or policy preferences. This study demonstrates that residential flexibility, when intelligently managed, can enhance energy efficiency and grid stability without large-scale infrastructure upgrades.

The large-scale integration of inverter-based renewable energy, such as wind power, into the Nordic power grid challenges operational security by reducing system inertia and short-circuit strength. This paper investigates and compares the effectiveness of two power electronic solutions: Battery Energy Storage Systems (BESS) and Enhanced STATCOMs (E-STATCOM), in mitigating these stability issues to support a reliable energy transition.

A two-part methodology with a focus on the Nordic grid was implemented, starting with a system-wide stability analysis using phasor domain simulations. This was followed by the implementation of a grid code compliance test framework in the time domain, which can be used to evaluate a wind plant's performance standalone and when paired with BESS or with E-STATCOM.

The findings affirm that the technical debate should shift from whether large-scale renewables can be integrated to how they can be supported most effectively. The results demonstrate that wind power, when paired with either BESS or E-STATCOM, can be effectively and reliably integrated into the grid, successfully mitigating the stability challenges that arise from displacing conventional synchronous generation. The paper concludes that while both solutions are highly beneficial, their optimal deployment is context-dependent. By providing an overview of their technical services and value propositions, this research offers critical insights for stakeholders to select the most appropriate technology for ensuring the reliable integration of large-scale wind power.

As power systems transition toward high shares of inverter based renewable generation, the way we define, assess, and ensure system stability must evolve. Traditional sources of inertia, synchronizing power, and voltage support are becoming less prevalent, while increasing power transfers and grid reinforcements push operation closer to technical stability limits. This presentation outlines the emerging challenges for system stability in renewables-based grids, including frequency, voltage, and rotor angle stability, and highlights the growing importance of stability constrained transfer limits. It discusses how regulatory frameworks can better integrate stability related assessments into operational planning and real time processes.

Agora Energiewende has been publishing an annual assessment of the development of German greenhouse gas emissions and the underlying trends for 10 years. In this session we will focus on the results concerning the power system: Build-out of PV and wind, grid development, electrification (in industry, heating, and mobility), and batteries. What are the major power market design changes being discussed?

Germany has set an ambitious target of reaching net zero greenhouse gas emissions by 2045. We explore how integrated cross-sectoral planning can reduce costs compared to existing national plans. Our new linear optimization model PyPSA-DE simulates the electricity and hydrogen transmission networks, as well as supply, demand, and storage in all sectors of the energy system in Germany and its neighboring countries with high spatial and temporal resolution. While our new model shows strong electricity transmission grid development, total expansion is one third lower than in the national grid development plan, lowering costs by 92 billion €_2020 to 191 billion €_2020 and average grid tariffs by 7.5 €2020/MWh. These savings are mainly due to integrated planning and operation, a market design with regional prices, and a system-optimal usage of offshore wind. PyPSA-DE is open-source and can readily be adapted to study related issues around the energy transition.

Adequacy 2050 - Security of Supply in the Power System

The Relevance of European Cooperation for a Cost-Effective Energy Transition - Deep insights from cross-sectoral energy system modelling

The large-scale integration of renewable energy requires upgrades to transmission infrastructure. Grid boosters (GBs) enable increased grid utilization through their curative congestion management capabilities and provide ancillary services. However, their reliance on battery storage makes them a costly solution. This paper investigates hybrid grid boosters (HGBs), which combine, in our case, a battery energy storage system (BESS), a hydrogen electrolyzer (HE), and a gas turbine. The hybrid design reduces BESS capacity, lowers capital costs, and increases operational flexibility.

A detailed and scalable physical dynamic model of the HGB is developed for stability analysis. The EMT model incorporates grid strength, represented through the short-circuit ratio (SCR), and the impact of the interaction between supply and demand on frequency, as well as the coupled electrical–thermal dynamics of the electrolyzer. It employs established representations (e.g., IEEE standard models) for the turbine, governor, and exciter. The dynamic power allocation control strategy is modified and applied to the adopted HGB approach. It enables seamless power sharing between the BESS and turbine, ensuring a reliable response under congestion events. The grid-forming electrolyzer is implemented and evaluated during frequency fluctuations.

Results demonstrate that HGBs can enhance the integration of renewables by providing additional (virtual) transmission capacity and long-term storage, while also supporting voltage and frequency ancillary services during non-congestion periods. The proposed model framework supports the deployment of HGBs to strengthen grid stability and improve the economic viability of future power systems.

The Charging Interface Initiative (CharIN e.V.) is leading the global effort to advance interoperable and scalable charging solutions for electric vehicles (EVs). With a focus on both the Combined Charging System (CCS) and the Megawatt Charging System (MCS), CharIN is shaping the future of high-power charging across passenger, commercial, and heavy-duty transport sectors.

CCS, now capable of delivering up to 1000 kW, supports fast and reliable charging for light- and medium-duty EVs. MCS, designed for ultra-high-power applications exceeding 3.75 MW, enables the electrification of demanding sectors such as logistics, mining, marine, construction, and aviation. Together, these technologies form a complementary ecosystem that supports the full spectrum of e-mobility needs.

CharIN and its members are the enabler of intelligent energy systems through the implementation of ISO 15118-20, which facilitates Vehicle-to-Grid (V2G) communication, Plug & Charge, smart charging, and secure data exchange. Through initiatives like V2G Testivals and its Grid Integration Focus Group, CharIN fosters collaboration among OEMs, CPOs, DSOs, TSOs, and aggregators to ensure seamless energy interaction.

To secure interoperability, CharIN has established a global Conformance and Interoperability Program. This includes structured testing frameworks, priority-based test cases, and certification via cross-certified labs. The CharIN Conformance Label serves as a trusted mark of quality and compatibility, supporting regulatory acceptance and market confidence.

By harmonizing standards, promoting cross-industry collaboration, and certifying reliable charging solutions, CharIN is laying the foundation for a connected, intelligent, and future-proof charging infrastructure—accelerating the transition to sustainable, zero-emission mobility worldwide.

This paper presents the real-world implementation and field validation of a user-aware, smart bidirectional electric vehicle (EV) charging system, developed for the Mobilities for EU and DymoBat projects in Dresden. Building on previous scenario-based modeling and simulation frameworks, the system takes a critical next step: enabling the transition from conceptual pilots to operational deployment in city contexts. To support increasing demands for grid flexibility and clean urban mobility, our solution couples real-time user and vehicle telemetry with a centralized optimization platform, achieving data-driven charging and discharging decisions. The architecture integrates a wireless On-Board Diagnostic II (OBD-II) interface and an open communication middleware node with a 5G campus network to furnish early, pre-connection access to vehicle state-of-charge, even before the vehicle is plugged in. Simultaneously, a tablet-based human-machine interface captures user preferences—such as desired departure time and energy needs—which inform optimization logic alongside grid conditions and mobility trends.

A key innovation is the closed-loop, multi-level communication architecture that links the user, the EV, the bidirectional charging station, and the grid control center, leveraging the Open Charge Point Protocol (OCPP) for seamless system integration. This design synthesizes software, embedded hardware, and networked components to deliver real-time, driver-inclusive charging management. Field deployment at Ostra Sport Park, located in the Dresden Ostra District, confirms the operational feasibility of the system, demonstrating improved load balancing and robust vehicle-to-grid (V2G) operation in practice. By enabling early data acquisition and proactive system management, the framework sets a benchmark for positive energy districts (PEDs) and climate-neutral city initiatives across Europe. This work represents the core technical result of Dresden’s pilot for the Mobilities for EU project, advancing the applied engineering and user-centered integration needed for the next generation of urban e-mobility systems.

This article describes different dynamic stability assessment tools and aspects to be considered in order to obtain comparable simulation results. A comparison between the simulation tools NEPLAN and DIgSILENT PowerFactory shows identical results for load flow calculations and contingency analysis. For dynamic studies using RMS simulations, the results for the event of a three-phase short circuit with fault clearing show very good agreements for the behaviour of the bus voltages, generator speeds, generator moments, and rotor angles. This article provides recommendations for software settings and models in order to obtain the highest level of agreement between the tools. Studies on critical fault clearing time show a difference between the tools of up to 15 ms which is related to the evaluation of the rotor angle stability of the critical generator nearby the short-circuit event.

P2P Energy Trading and Labelling of Green Energy

For the TSO TransnetBW E-Mobility is an important topic. TransnetBW expects a hugh amount of such decentralized flexibility, which affects system planning, security of supply and more. Therefore, TransnetBW aims for a full integration of these assets into markets, procedures and the grid, which includes the use case of market-based redispatch. During the presentation, the motivation of TransnetBW and the opportunities for market parties are further explained. Pilot projetcs of TransnetBW and its partners will presented. At the end, a few open questions will serve as a basis for further discussions.

EV Grid Integration in Norway

This paper presents the concept and premises of a pilot plant for a megawatt (MW) charging station developed in Stord, Norway, under the MegaCharge project. The charging system comprises containerized charging modules designed for heavy-duty transport, integrating battery energy storage systems (BESS) that supply power alongside the grid. A technical description of the converters for both systems is provided, including their control strategies and operational specifications. The pilot plant testing and evaluation methodology is described, including several testing cases as black out and earth faults, thermal limits, showcase of the megawatt charging system (MCS) plug, dynamic test of the energy management system (EMS) with MCS Emulator, and other faults and circuit breaker actions. The depiction of the pilot plant offers a foundation for future research and practical implementation.

Electrifying the heavy-duty vehicle (HDV) segment involves more than just substituting the technological solution; it also requires rethinking operational practices and developing digital solutions that support seamless logistics. This study investigates user needs and explores alternative concepts for booking systems for charging of electric HDVs. Based on a literature review, an analysis of relevant standards and protocols, and interviews with key stakeholders including logistics managers, planners, drivers, technology providers, and public authorities, this study identifies the key requirements for developing interoperable and user-centric booking systems for HDV charging. Insights suggest placing emphasis on avoiding digital fragmentation through the adoption of open standards, roaming, real-time data sharing, and integration with fleet and energy management systems. To illustrate potential paths forward, the study outlines three conceptual models for booking systems aiming to facilitate an accelerated and scalable charging infrastructure roll-out for HDVs in Europe and beyond.

Systemstability - Another Angle: Regulatory Perspective

Workshop Welcome

The integration of water electrolyzers into the electrical energy system is a key component of the energy transition. In the past, electrolyzers were being connected to the grid solely as consumers. However, large-scale electrolysis units with connected loads exceeding several hundred megawatts have a considerable impact on grid stability. Given the decreasing number of connected thermal power plants (nuclear, gas, and coal), the high total installed capacity planned, and the slow progress in expanding transmission infrastructure, grid code compliance with more demanding requirements for electrolyzers will become increasingly important. Transmission system operators (TSOs) impose strict requirements on the grid compatibility of electrolyzers. With appropriate system design, the next generation of electrolyzers can not only produce hydrogen but also contribute significantly to the stability of the electrical grid and, consequently, to the security of supply.

Australia’s electricity system is undergoing rapid transformation. Rooftop solar, electrification, and localised energy use are increasing, while grid-scale generation and transmission projects face delivery delays. For Ausgrid—Australia’s largest distribution network operator serving 4 million people—this creates both risk and opportunity.

To respond, Ausgrid is deploying a portfolio of distribution-connected community batteries, typically 5 MW in size and co-located with substations. Backed by innovation funding from the Australian Renewable Energy Agency (ARENA), these batteries are designed as shared infrastructure—unlocking system value while supporting equitable customer access. Ausgrid’s network-led ownership model ensures battery capacity is prioritised for regulated network services, with spare capacity contracted for market or customer use.

This presentation outlines Ausgrid’s approach to scaling community batteries as a new asset class. It includes:

A structured framework for quantifying over 30 network use cases, including deferral of augmentation, voltage support, transmission demand reduction, and improved DER hosting

A practical reservation model to allocate and prioritise network services

Standardisation of layout, connection, and control processes to enable repeatable deployment

Development of a technology and commercial partner ecosystem, including non-lithium options

An inclusive customer access model via Energy-Storage-as-a-Service (ESaaS), enabled by Local Use-of-System (LUOS) pricing (innovation trial tariff)

Internal analysis suggests shared community batteries could reduce system costs by up to $25 billion if they replace even half of expected household battery uptake in NSW.

This session will share lessons from Ausgrid’s operational fleet, rollout strategy, and evolving delivery model—demonstrating how distributed batteries can become flexible, scalable grid infrastructure that delivers for customers, the grid, and the system.

Assessment of the DSM potential on two sample islands (DSM4islands)

Designing Grid Connection Requirements for Small-Scale Generation in Developing Countries

eMobility Development in Germany

China’s Electrification in the Mobility Sector

Demand Flexibility and Large Loads

Germany’s rapid expansion of renewable energy—particularly small-scale photovoltaic (PV) solar systems—has led to an increasing risk of generation surpluses in Germany. Since 2022, nearly 40GW of photovoltaic capacity has been added, reaching more than 100 GW in 2025. Renewables now account for approximately 60% of electricity consumption, with projections indicating 80% by 2030 and installed capacity exceeding 300 GW.

This rapid growth necessitates a more robust market and system integration of renewable energy sources. However, current regulatory frameworks and limited digitalization hinder the responsiveness of renewable assets to market signals. While direct marketing models incentivize curtailment during negative price periods, many installations, especially those under grid operator marketing, remain often non-controllable and are fully dispatched regardless of price signals.

The 2025 System Stability Report by German transmission system operators highlights that without improved integration, the affordability and security of the energy transition are at risk. Increasing occurrences of negative electricity prices (over 450 hours in 2024) and declining market values result in higher subsidy costs. Furthermore, the uncontrolled feed-in from small-scale PV systems increase the risk of overloads in the transmission and distribution grid as well as over-frequency situations, which can jeopardize the security of supply.

Transmission system operators expect surplus generation situations to arise in the coming years. To ensure security of supply in these situations, grid operators must be able to control the feed-in from small-scale PV systems. In the medium term, it will be necessary to be able to measure and control systems with an installed capacity of 7 kW or more. In addition, the subsidies and marketing of renewable energies must be further developed in such a way that no feed-in takes place when electricity prices are (significantly) negative.

The so-called 2025 peak electricity package has introduced new rules to prevent generation surpluses. These are intended to improve the controllability of small-scale plants, make the use of storage facilities more attractive, and improve feed-in tariffs and marketing in the event of negative prices.

In conclusion, addressing generation surplus requires a coordinated approach involving regulatory reform, digital infrastructure, and technical innovation. Enhanced controllability, data quality, and market responsiveness are essential to ensure the economic viability and system reliability of a renewable-dominated energy landscape.

Globally, the imperative to integrate power grids is intensifying as renewable integration, extreme weather, and rapid electrification strain reliability and raise costs. Yet building inter-regional transmission is challenging: jurisdictions struggle to coordinate planning, allocate costs equitably, design trading frameworks, and secure community license. Europe, Australia, Canada, and the United States each face these pressures from different starting points, offering valuable lessons in both success and failure. This paper consolidates insights from more than one hundred interviews with grid operators, utilities, policymakers, and academics worldwide, alongside a review of international planning and regulatory processes. It identifies emerging best practices across five pillars: governance, planning, trading, financing, and community engagement. Case studies highlight how Europe and Australia’s structured planning processes, U.S. cost-allocation debates, and Canada’s Indigenous-led partnerships each illuminate different pathways to overcome barriers. By comparing diverse approaches, the paper distils strategies that have proven effective in advancing inter-regional transmission: transparent governance, harmonized planning, neutral trading interfaces, beneficiary-pays financing, and genuine community participation. These insights provide a roadmap for policymakers and system planners to accelerate grid integration, enhance resilience, and enable the clean energy transition.

High resolution projections for load and generation growth in distribution networks

In our study, an hourly dispatch analysis using the software SDDP is conducted to investigate and compare different expansion scenarios to strengthen the Peruvian transmission system until 2036 in the context of increasing shares of variable renewable energy connections and increasing electricity demand. A special focus lies on the Southern region, which will experience large amounts of new PV installations and the expansion of its mining industry. The assessed solutions are i) battery energy storage systems, ii) reinforcement of the AC network between Southern and Central Peru and iii) additional construction of High-voltage DC transmission. Our findings suggest cost-competetiveness of HVAC and HVDC solutions and show pathways when and how storage and transmission solutions can complement existing HVAC transmission systems.

How to handle European grid complexity and runtime in PyPSA

Grid Integration of Large Loads

The shift toward sustainable renewable energy coming with converter-based generation has significantly reduced system inertia introducing serious challenges in maintaining voltage and frequency stability, particularly under weak grid conditions with low short-circuit ratios. While grid-forming converters are under active development to address these issues, there remain challenges to overcome on the road to maturity and widespread commercial deployment. Our proposed solution, Unified Advanced Vector Control (UAVC), is specifically designed to operate with grid-following converters – and can be added as a software-only retrofit to converters already in service. Adding UAVC enhances converters’ stability and, in many cases, reduces or could even eliminate the need for expensive reactive compensation devices such as synchronous condensers.

Unlike classical control approaches, UAVC is based on a single fixed-parameter robust controller that guarantees stable performance across a wide range of grid strengths and operational conditions. In addition, the UAVC framework can be adapted to support grid-forming operation providing a unified path toward stabilising both existing and future converter-dominated networks.

Accurate intraday solar forecasts are crucial for electricity trading and microgrid management. While satellite-based methods outperform numerical weather prediction (NWP) models for short-term horizons, their accuracy depends heavily on stable weather conditions, performing poorly during convection, fog, or large depressions. This study investigates the impact of various North Atlantic weather regimes—Atlantic Ridge, Scandinavian Blocking, NAO+, and NAO-—on the reliability of satellite-based forecasts.

We conducted an 8-year backtest using forecasts generated four hours ahead with a 15-minute time step and validated them against pyranometer data. Our analysis shows that forecast errors vary significantly with the prevailing weather regime. The difference in relative RMSE between the Scandinavian Blocking and Atlantic Ridge regimes was 10-12% in summer (2016-2020) and approximately 10% after 2020. In winter, this difference was around 20% before 2020 and 15% after 2020. These findings demonstrate that large-scale atmospheric patterns significantly influence forecast reliability. Given that weather regimes can be predicted in advance, this analysis provides valuable insights for anticipating forecast error, which can help optimize PV integration and serve as a useful input for machine-learning-based forecast algorithms.

These variations in weather regime frequencies directly impact forecast errors, emphasizing the importance of large-scale atmospheric patterns in solar energy forecast reliability. As weather regimes can be predicted several days in advance, this analysis provides useful information to anticipate the magnitude of forecast error and therefore adapt suitable decisions for optimizing PV integration management and electricity trading and provide important insights to develop deep learning forecast algorithms

In the OctoFlexBW project, energy provider Octopus Energy and transmission system operator TransnetBW are pioneering redispatch services by harnessing aggregated flexibility from residential electric vehicles within the TransnetBW control area. By intelligently shifting overnight charging, the initiative delivers cost-efficient grid relief through a fully integrated, scalable end-to-end process.

First Stability Report of German TSOs according to §12i EnWG

Germany's Roadmap System Stability - Highlighting selected challenges, achievements and milestones

The rapid electrification of heavy-duty vehicle (HDV) fleets requires a significant increase in high-power charging infrastructure along highways. This expansion is closely linked to available electricity grid capacity and stability, making it a critical challenge for the transition to more sustainable mobility and electricity systems. Coordinated fleet charging offers significant potential for increasing the system reliability. It can reduce the need for costly grid reinforcements and actively contribute to grid stability, thus supporting the grid to cope with challenges from intermittent electricity provision from wind and solar. Initial analyses indicate that HDV fleets that charge during periods of low demand, align with renewable generation patterns, and avoid peak demand increases can realize significant economic benefits. Our future research investigates how providing real-time ancillary services including congestion management and dynamic stability services reduces infrastructure stress and creates new market opportunities for fleet and system operators.

We are developing a collaborative research project to explore how dynamic toll pricing, in combination with dynamic electricity tariffs, can incentivize grid-friendly HDV operations. The project will: (1) investigate system-oriented scheduling strategies for HDV fleets, (2) develop algorithms that co-optimize logistics and charging operations simultaneously and under consideration of grid-stability, and (3) analyze business cases for dynamic tolls and flexibility services in real-world scenarios. We built upon our extensive expertise in integrated modeling of sector-coupled energy systems. For example, we developed the open-source tool venco.py, which derives charging flexibility potentials from mobility data and, in combination with energy system optimization (e.g. our open-source energy system model REMix), identifies grid expansion needs. Furthermore, our agent-based model AMIRIS allows us considering future electricity market prices.

With our poster, we want to discuss our concept for jointly assessing technological, economic, and operational opportunities for cost-efficient, future-ready HDV electrification.

Germany's System stability Roadmap

Solar energy forms an important pillar of climate change mitigation. Short-term

forecasts of surface solar irradiance (SSI) are gaining more importance for power grid

operators seeking to balance supply and demand in a secure and economical way.

Regional-scale SSI forecasts are essential since most solar power is provided by

decentralized PV plants. Regional-scale SSI estimates can be obtained from infrared

and visible Earth imagery of geostationary satellites such as Meteosat. Solar nowcast

models oEer SSI predictions at forecast lead times of minutes to hours. Current

regional-scale solar nowcast models often require satellite-derived SSI products based

on SSI satellite retrievals like Heliosat SARAH-3. Moreover, current solar nowcast

models are typically deterministic, lacking the ability to quantify forecast uncertainty.

I provide an overview of recent developments in spatiotemporal forecasting of solar

energy across Europe. For example, I will introduce the first two regional-scale solar

nowcast models, SolarSTEPS and SHADECast, which provide probabilistic satellitebased

solar forecasts for minutes to hours ahead (Carpentieri et al., 2023, 2024). Our

models simulate multiple forecast realisations for any given time and location which

enables accurate forecasts and uncertainty quantification for regions up to thousands

of kilometers in size. Our solar nowcast models perform autoregressive and generative

AI simulations. We demonstrate that they enhance forecast accuracy under all

cloudiness conditions. Our generative SHADECast model enhances the forecast

horizon of the state-of-the-art SolarSTEPS model by 26 minutes for lead times of up to

two hours. Additionally, we present a deep learning emulator of the Heliosat SARAH-3

SSI product (Pfeifroth et al., 2021), which predicts kilometer-scale SSI estimates at 15-

minute intervals based on visible and infrared Meteosat imagery. The emulator, a

convolutional residual network, estimates instantaneous SSI across Europe with

accuracy comparable to SARAH-3. It even surpasses SARAH-3 in SSI accuracy when

retrained on pyranometer stations (BSRN, IEA-PVPS, national weather services),

allowing for more accurate SSI initialization of solar nowcast models.

Hvide Sande – what can Germany learn from Denmark in Heat and Power Integration?

This presentation will describe the use of Q/V and P/ frequency scans for grid-forming (GFM) resources to quantify their contribution to grid strength. Grid strength contributions from various GFM resources including battery energy storage systems (BESS) based on inverters with GFM controls and synchronous condensers will be compared using this approach. It will be shown that SynCons provide highest grid strength contributions for the same rated capacity compared to BESS plants. It will be shown that while the grid strength contributions from different GFM BESS resources from different vendors can be different, they generally fall within a narrow range, which can be used for planning purposes when vendors for GFM vendors are not yet identified.

High shares of PV - Texas

The Role of Battery Storage in the Energy System

Regulatory and Technical Barriers to Break for Succesfull V2G Implementation

System Stability through Grid-forming Units - Requirements in the Context of the Procurement of Inertia

Integration of Photovoltaic into Electricity Networks and Markets – Overview of the new IEA PVPS Task 19

Task 19 of the IEA PVPS program is dedicated to the integration of photovoltaics (PV) into power grids with the aim of establishing PV as the central pillar of a fully renewable energy system. Building on the experiences from Task 14, Task 19 was launched in 2024 to address technical, regulatory and economic challenges of PV network integration. More than 50 experts from 20 countries have defined 25 activities in nine research fields in five workshops, including topics such as grid capacity, prosumer rights, smart grids, inverter technologies and local energy markets.

The international network started in 2025 with 40 nominated experts from 18 countries to work on:

• National PV Targets vs. Grid Capacity​
• Rights and Obligations of Prosumers​
• PV in the Smart Grid​
• Registration and Commissioning​
• Curtailment – Power Management​
• New Inverter Capabilities​
• Aggregators, Local Markets and Energy Communities​
• Local Energy Management​
• Energy Economy in a 100% RES Based Power System​

The aim is to identify and overcome barriers to the implementation of national PV expansion targets, for example by developing hosting capacity models, new inverter capabilities (e.g. Grid-forming), as well as by promoting aggregators and energy communities. An agile working approach with "Joint Research Activities" enables flexible, result-oriented collaboration. Task 19 also strives for a stronger digitization of dissemination, for example through a lively online platform in addition to classic technical reports.

The results are intended to help decision-makers, network operators, manufacturers and prosumer organizations to integrate PV efficiently and sustainably into future electricity networks and markets.

Immittance-Based Frequency-Domain Modeling: A Framework to Achieve System Stability

To meet ambitious climate goals, power systems are experiencing significant transition towards clean, low- carbon technologies. This transformation is characterized by a growing share of inverter-based resources, which are now present across all parts of the system including generation, transmission and load. Wind and solar power plants are widely deployed on the generation side, as well as HVDC interconnectors and STATCOMs at the transmission level. On the load side, electrolysers and large-scale data canters are expected to grow significantly in the coming years. In addition, Battery Electric Storage Systems (BESS) are being deployed as bidirectional units that can act as both generation and load.

All of these technologies interface with the grid through power electronic converters, which behaviour is mostly driven by control algorithms. This control-driven behaviour adds significant complexity to the overall system dynamics. As a result, the increasing complexity of the grid combined with practical experience gained from system operation and completed projects, highlights the need for continuous refinement of grid connection requirements with respect to system needs and functions, system studies and models.

This paper addresses these challenges by focusing on frequency-dependant impedance behaviour and corresponding analysis across the frequency range of interest starting from 0 Hz up to 2500 Hz. While updates to other system needs and functions as well as study requirements are also being made in response to the evolving grid environment, this paper concentrates specifically on defining HVDC Sub-Synchronous Oscillation (SSO) damping capability and damping performance above 100 Hz, along with the corresponding system studies required to demonstrate compliance with these requirements

Energy Transition: Current State and Challenges from a TSO's Perspective

ENTSO-E's Report on Technical Requirements for GFM Capabilites of PPMs

The Growing Role of Flexibility in Modern Power Systems

CROF (Control Room of the Future) - tbc