Integrated Energy System Operation Optimization Based on Reinforcement Learning. Issue 1 (1st February 2022) - Wang, Yongli; Dong, Huanran; Xu, Miaomiao; Cai, Chengcong; Yao, Suhang; Ma, Yang; Li, Shuquan
Abstract: Each subject in the integrated energy system has different interests and demands, and it is necessary to optimize the energy dispatching with the help of multi-subject game theory. In order to solve the above problems, this paper proposes a reinforcement learning-based multi-object operation optimization method for integrated energy systems. Firstly, a multi-subject integrated energy system model including energy suppliers, park service providers and users is constructed; secondly, a game search method based on reinforcement signals is proposed to improve the speed of multi-subject game solution; finally, a simulation is conducted with an integrated energy system as an example to verify the effectiveness and rapidity of the proposed method.