Optimizing Multi-Microgrid Operations with Battery Energy Storage and Electric Vehicle Integration: A Comparative Analysis of Strategies - Syed Muhammad Ahsan; Petr Musilek (Batteries)
This study presents a comprehensive comparative analysis of the operational strategies for multi-microgrid systems that integrate battery energy storage systems and electric vehicles. The analyzed strategies include individual operation, community-based operation, a cooperative game-theoretic method, and the alternating direction method of multipliers for multi-microgrid systems. The operation of multi-microgrid systems that incorporate electric vehicles presents challenges related to coordination, privacy, and fairness. Mathematical models for each strategy are developed and evaluated using annual simulations with real-world data. Individual operation offers simplicity but incurs higher costs due to the absence of power sharing among microgrids and limited optimization of battery usage. However, individual optimization reduces the multi-microgrid system cost by 47.5% when compared to the base case with no solar PV or BESS and without optimization. Community-based operation enables power sharing, reducing the net cost of the multi-microgrid system by approximately 7%, as compared to individual operation, but requires full data transparency, raising privacy concerns. Game theory ensures fair benefit allocation, allowing some microgrids to achieve cost reductions of up to 13% through enhanced cooperation and shared use of energy storage assets. The alternating direction method of multipliers achieves a reduction in the electricity costs of each microgrid by 6–7%. It balances privacy and performance without extensive data sharing while effectively utilizing energy storage. The findings highlight the trade-offs between cost efficiency, fairness, privacy, and computational efficiency, offering insights into optimizing multi-microgrid operations that incorporate advanced energy storage solutions.