%0 Journal Article
%T 基于柔性行动器–评判器的电–热综合能源系统协调优化<br>Coordinated Optimization of Integrated Electricity-Heat Energy System Based on Soft Actor-Critic
%A 刘雨
%A 董雷
%A 王春斐
%A 李梦婷
%A 乔骥
%A 王新迎
%J Smart Grid
%P 107-117
%@ 2161-8771
%D 2021
%I Hans Publishing
%R 10.12677/SG.2021.112011
%X <div style=\"text-align:justify;\">
	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。<br />
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.
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%K 电–热综合能源系统，优化调度，深度强化学习，柔性行动器–评判器<br>Integrated Electricity-Heat Energy System
%K Optimal Dispatch
%K Deep Reinforcement Learning
%K Soft Actor-Critic
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=41477