作为新型电力系统的重要组成部分，多微网的能量交互共享有利于可再生能源的消纳和多主体运行效益的提升。针对多微网的源荷不确定性及数据隐私问题，提出一种基于能量共享的多微网协同优化调度方法。首先，构建基于多主体交互框架的共享储能和微网经济调度模型；然后，通过深度强化学习方法和数学启发式方法，实现共享储能的充放电功率定价策略和多微网的经济调度决策；最后，仿真数据分析表明所提协同优化调度方法能够快速应对源荷随机变化，同时有效降低了多微网运行成本。

As an important part of the new power system, the energy interaction and sharing of multi-microgrids are conducive to the consumption of renewable energy and the enhancement of multi-agents operation efficiency. Aiming at the multi-microgrids source-load uncertainty and data privacy problems, a multi-microgrids cooperative optimal scheduling method based on energy sharing is proposed. Firstly, a shared energy storage and microgrid economic dispatching model based on a multi-agent interaction framework is constructed. Then, the power pricing strategies for shared energy storage and the economic scheduling decisions for multi-microgrids are realized by deep reinforcement learning method and mathematical planning method, respectively. Finally, simulation data analysis shows that the proposed cooperative optimal scheduling method can quickly cope with the stochastic variation of source-load, as well as effectively reduce the operation cost of multi-microgrids.