The design of battery and grid solutions for industrial microgrids presents significant challenges due to fluctuating industrial loads and the increasing integration of renewable energy sources (e.g., wind and solar). Determining the optimal battery size is critical for effective energy management, ensuring sufficient storage capacity to balance supply and demand without oversizing, keeping capital expenditures within a reasonable limit. At the same time, designing the grid requires selecting appropriate cable types and capacities that can accommodate varying load profiles and operation scenarios while minimizing both capital and operational costs. Engineers have to consider the interplay between system performance and economic viability, analyzing load patterns, generation profiles, and real-time operation conditions. Addressing these multi-dimensional challenges is pivotal for achieving robust, cost-effective solutions in industrial microgrid applications, ensuring reliability, efficiency, and sustainability under dynamic operating environments.

These design tasks are difficult for a number of reasons. First, solar and wind power are highly dependent on weather conditions and time of day, while, on the other hand, industrial processes can introduce sharp and unpredictable load variations. These mismatches between energy supply and demand complicates the efforts to maintain reliability and stability within the microgrid. Second, the optimal design of battery and grid systems becomes even more challenging under such uncertainties. Moreover, effective sizing must consider detailed operational optimization during the pre-FEED phase, evaluating the system behavior over time across different scenarios. Finally, this level of analysis is computationally intensive and time-consuming. It often requires high-resolution data and extended simulation periods, which, in practice, often slows down early decision-making and complicate the evaluation of multiple design alternatives.

In this work, we propose an interactive pre-FEED analysis on the integration of renewables and energy storage. We demonstrate how grid requirements can be integrated based on a literature-based approach and how a high-level, quick pre-FEED analysis can be combined with a deep insight into operational optimization of the assets. We demonstrate our approach based on a mining use case, where diesel as the traditional source of energy shall being replaced by renewable energy during electrification efforts. Since mining combines remote microgrids with large and fluctuating loads (especially, the electrification of material transportation) and a high potential for reducing CO2 emissions, this use case is suited to outline the main challenges and opportunities of the energy transition. The proposed pre-FEED tool comes at the benefits of an interactive design and fast performance, so that customers can assess both (i) an overall recommendation for battery power and capacity, and (ii) a detailed analysis of solar, wind and battery usage during operation of the mine.