Coordinated Optimization of Integrated Electricity-Heat Energy System Based on Soft Actor-Critic

电–热综合能源系统的优化调度对于实现系统的能源互补、经济运行具有重要意义。本文提出一种基于柔性行动器–评判器(Soft Actor-Critic, SAC)算法的电–热综合能源系统经济调度方法，首先针对电–热综合能源系统优化调度问题进行建模，然后基于SAC框架将该问题转化为强化学习模型，搭建了强化学习环境。最后对基于SAC的电–热综合能源系统优化运行解结果进行分析，并进一步验证该方法的有效性。 The optimal dispatch of integrated electricity-heat energy system (IEHS) is of great significance to the energy complementation and economic operation of the system. An economic dispatch method for IEHS based on the Soft Actor-Critic (SAC) algorithm is proposed in this paper. Firstly, an optimal dispatch model of IEHS is established, and then the problem is transformed into a reinforcement learning model based on the SAC framework, and a reinforcement learning environment is built. Finally, the optimal operation result of integrated electricity-heat energy system based on SAC is analyzed, and the simulations show that the proposed method can effectively solve the problem and reduce the operation cost.