Integrated Energy System Operation Optimization Based on Reinforcement Learning

Abstract Each subject in the integrated energy system has different interests and demands, it is necessary to optimize dispatching with help of multi-subject game theory. In order solve above problems, this paper proposes a reinforcement learning-based multi-object operation optimization method for systems. Firstly, model including suppliers, park service providers users constructed; secondly, search based on signals proposed improve speed solution; finally, simulation conducted an as example verify effectiveness rapidity method.