Distributed coordinated optimization of the community energy system considering energy sharing and benefit allocation

With the continuous increase in renewable energy penetration, community energy consumers evolve into prosumers capable of both producing and consuming energy. However, renewable intermittency leads to supply-demand imbalances, undermining system economics. To enhance local renewable energy utilization and improve economic efficiency, this study proposes a distributed coordinated optimization strategy integrating flexibility resource management, energy sharing, and benefit allocation. First, mathematical models of flexibility resources are established. Second, a hybrid centralized-decentralized energy sharing framework is developed, which is solved using a distributed sequential algorithm to ensure computational scalability and user privacy while maximizing collective benefits. The framework reduces community operational costs by 39.66% in summer and 22.28% in winter. Finally, to ensure a fair allocation of benefits from energy sharing, a heuristic allocation scheme is designed. This scheme adapted from the Vickrey-Clarke-Groves mechanism evaluates the marginal contributions of users and incentivizes truthful reporting of cost parameters during strategic interactions. The results show that 55.15% of total benefits are allocated to prosumers and 44.85% to consumers, achieving full user satisfaction and highlighting the substantial advantages of the proposed model. This research aims to offer guidance for building efficient and equitable community energy systems.