Abstract: The widespread integration of user-side renewable energy and shared energy storage has outpaced the flexibility of existing operational models and led to unreasonable allocations of energy-sharing benefits. This study aimed to develop an optimized operational model for community microgrid alliances that accommodated diverse service demands and power exchange. First, a system framework for the coordinated operation of shared energy storage and community microgrid alliances was established. Second, based on a Stackelberg game balancing the interests of both the shared energy storage operator and community microgrid alliances, a nested RIME algorithm integrated with the Gurobi solver was employed to determine day-ahead scheduling decisions, community operating costs, energy storage pricing decisions, and operational revenues. Third, in the day-ahead scheduling stage, power exchange among communities was considered by computing allocation coefficients from the similarity between community renewable generation outputs and load profiles, the magnitude of power exchange, and their correlation; these coefficients were then used in a weighted-contribution method to reallocate day-ahead operating costs among communities. Finally, case-study simulations validate the effectiveness and applicability of the proposed model.