Shared energy storage with multi-microgrids: Coordinated development and economic–social–environmental comprehensive assessment under supply–demand uncertainties

Coordinated development of multi-microgrids and shared energy storage optimizes resource allocation, enhances renewable energy utilization, and mitigates environmental impacts. However, stakeholder conflicts and supply–demand uncertainties pose significant challenges. This study proposes a bi-level interaction framework for coordinated planning, optimizing shared energy storage pricing via genetic algorithms to determine optimal leasing, scheduling, and configuration strategies, exhibiting strong scalability and adaptability in large-scale systems. Wasserstein metric-distributed robust optimization and stochastic planning address supply–demand uncertainties, enhancing robustness and reducing the model’s over-conservatism. Leveraging complementary charging and discharging behaviors, the model minimizes storage investment, improves resource utilization, stabilizes the system, and achieves over 95% renewable energy absorption, fostering a sustainable business model. Given the diversification of energy storage technologies, a rigorous value assessment method is essential. This study constructs an economic–social–environmental evaluation framework for shared energy storage based on life cycle thinking, externality theory, and sharing economy principles. Employing the analytic hierarchy process, the framework quantifies stakeholder benefits, responsibility allocation, and profit potential, including arbitrage from off-peak storage and peak-time discharge, grid pressure alleviation, and enhanced renewable energy integration. Finally, analysis of subsidy policies and the positive externalities of expanding peak-to-valley differentials offers policy insights for cleaner, more resilient, and sustainable energy systems.