HYB25-8
Automated Planning of Microgrids at Distribution Grid Level to Resupply Critical Infrastructure during a Blackout
02 HYB25-8
Presented by: Jakob Wieland
University of Wuppertal, Institute of Power Systems Engineering, Germany
Automated Planning of Microgrids at Distribution Grid Level to Resupply Critical Infrastructure during a Blackout
Jakob Wieland, Giuseppe Puleo, Maximilian Mütherig, Markus Zdrallek
University of Wuppertal, Institute of Power Systems Engineering, Germany
The increasing frequency of climate disasters raises the risk of widespread power outages (blackouts) and presents significant challenges to power grids, especially for the supply of critical infrastructures. This study aims to develop and implement an automated software solution for the planning of microgrids at distribution level to resupply critical infrastructure during a blackout. This software calculates all possible switching operations that are necessary to build up a microgrid at distribution grid level.
This study is based on the use of the IEEE 9-Bus system as a test environment. Furthermore, a real distribution grid was used for software validation. The software, developed in MATLAB and Python, is designed to read grid data, plan the microgrid, perform load flow calculations, and generate all required switching actions. The software ensures that the load on all grid components remains within predefined limits during the setup of the microgrid. In the real grid, the frequency drop and the operating point within the generator performance diagram of the black-start-capable power plant are evaluated.
The developed software includes a sequence of switching operations as well as the automated planning to build up a microgrid within a distribution grid during a blackout. Additionally, specific challenges related to reactive power management during grid restoration in real grids were identified. Simulations on a real distribution grid demonstrate the efficiency and applicability of the developed software.
The work's relevance lies in its potential to optimize grid restoration processes within distribution grids, ensuring a more resilient response to blackouts and enhancing the reliability of energy supply. By focusing on the automated planning of microgrids this study enhances the efficiency, stability, and security of grid recovery processes, especially in response to future grid disruptions caused by climate events and cyber-attacks on the transmission grid.
Jakob Wieland, Giuseppe Puleo, Maximilian Mütherig, Markus Zdrallek
University of Wuppertal, Institute of Power Systems Engineering, Germany
The increasing frequency of climate disasters raises the risk of widespread power outages (blackouts) and presents significant challenges to power grids, especially for the supply of critical infrastructures. This study aims to develop and implement an automated software solution for the planning of microgrids at distribution level to resupply critical infrastructure during a blackout. This software calculates all possible switching operations that are necessary to build up a microgrid at distribution grid level.
This study is based on the use of the IEEE 9-Bus system as a test environment. Furthermore, a real distribution grid was used for software validation. The software, developed in MATLAB and Python, is designed to read grid data, plan the microgrid, perform load flow calculations, and generate all required switching actions. The software ensures that the load on all grid components remains within predefined limits during the setup of the microgrid. In the real grid, the frequency drop and the operating point within the generator performance diagram of the black-start-capable power plant are evaluated.
The developed software includes a sequence of switching operations as well as the automated planning to build up a microgrid within a distribution grid during a blackout. Additionally, specific challenges related to reactive power management during grid restoration in real grids were identified. Simulations on a real distribution grid demonstrate the efficiency and applicability of the developed software.
The work's relevance lies in its potential to optimize grid restoration processes within distribution grids, ensuring a more resilient response to blackouts and enhancing the reliability of energy supply. By focusing on the automated planning of microgrids this study enhances the efficiency, stability, and security of grid recovery processes, especially in response to future grid disruptions caused by climate events and cyber-attacks on the transmission grid.