Decentralized Integrated Energy Management for Residential Users Based on Evolutionary Game

With the development of integrated energy systems (IES) and smart home systems (SHS), it is very important to effectively grasp the energy consumption behavior and habits of thermal users for the optimal allocation and utilization of energy. However, The energy consumption behavior has the characteristics of randomness and autonomy. Traditional game methods and optimization methods assume that players are rational, which is contrary to the actual situation. To this end, this paper presents a dynamic analysis model to analyze comprehensive energy consumption behavior of residential users based on the evolutionary game theory (EGT), and classifies the terminal user loads according to their energy demand and energy carrier units characteristics, and constructs a cost/payoff model. In the proposed model, the user updates the energy consumption strategy continuously through the revision protocol, and the dynamic process of the user energy consumption strategies is studied by solving the mean dynamic function. And we propose an algorithm based on EGT. The simulation results show the feasibility of the proposed method.