Two-stage robust optimization of shared energy storage system in multi-community energy systems considering electric vehicle flexibility

The variability of renewable energy and the increasing integration of electric vehicles (EVs) pose significant challenges to the planning and operation of multi-community energy systems. Shared energy storage systems (SESS) have emerged as an effective solution to enhance flexibility and improve system performance. In this study, a multi-community SESS planning and operation optimization framework considering EV participation is developed to determine the optimal storage configuration and operational strategies. First, an electric vehicle cluster (EVC) dispatchable capacity model is constructed to capture EV users’ willingness to participate in scheduling and aggregate the dispatchable capacity of EVC. Then, based on EVC dispatchable capacity, a two-stage robust optimization model is formulated to optimize multi-community SESS planning and system operation under renewable uncertainty. Case studies show that compared with benchmark strategies, the proposed method reduces SESS investment costs by 7.7% and decreases peak grid electricity purchase by 31.56%. In addition, system performance remains stable under renewable fluctuations. The results highlight the potential of SESS combined with EV flexibility for improving the economic performance and resilience of future community energy systems.