Stochastic chance-constrained multi-objective optimization of interconnected multi-microgrids: Diverse energy storage configurations and interaction scenarios

With the increasing penetration of renewable energy sources, interconnected multi-microgrid (multi-MG) systems have emerged as a promising paradigm to enhance energy flexibility and improve renewable energy utilization. However, their coordinated operation remains challenging due to coupled energy interactions, heterogeneous energy storage configurations, and inherent uncertainties in renewable generation and load demand. To address these issues, this paper develops a stochastic chance-constrained multi-objective optimization framework for interconnected multi-MG systems. The proposed framework aims to systematically investigate how energy storage deployment and inter-microgrid interaction structures influence system-level economic performance, environmental impact, and energy utilization efficiency under uncertainty. A stochastic chance-constrained formulation is employed to model uncertainties in renewable generation and load demand, which is transformed into deterministic equivalents under a predefined confidence level to ensure operational reliability. A multi-objective optimization model is then established to capture trade-offs among economic cost, energy efficiency, and environmental impact, and the ε-constraint method is adopted to generate a Pareto optimal solution set. A hybrid entropy weight-analytic hierarchy process-technique for order preference by similarity to ideal solution decision-making approach is further applied to identify the most balanced solution. Case studies on three interconnected microgrids are conducted to evaluate multiple energy storage configurations and interaction scenarios. The results show that proper energy storage deployment significantly enhances energy utilization rate by up to 25.91% and reduces carbon emissions by up to 25.92%, albeit with an 11.20% increase in investment cost. In addition, inter-microgrid interactions improve operational flexibility, reducing total economic cost by 2.70% under fully interconnected conditions compared to isolated operation. Furthermore, system performance is highly robust to single-link disruptions, while multi-link disconnections lead to more noticeable performance degradation.