Multi-game optimization strategy for virtual power plants considering EV user service selection

With the transformation of energy structure and the deepening of the concept of sharing economy, the large-scale access of electric vehicles (EVs) and the coordinated development of multiple virtual power plants (VPPs) have become an important trend to enhance the flexibility of power grids. However, the problems of multi-agent coordinated optimization and diversified charging demand of EVs need to be solved urgently. This paper proposes a multi-agent coordinated optimization operation strategy of VPPs that considers EV user service selection and multiple games. First, in view of the diversified charging needs of users, differentiated services including disordered charging, semi-flexible dispatch and full flexible dispatch are designed, and an evolutionary game model based on Logit dynamic protocol is established to simulate the non-completely rational decision-making behavior of users. Secondly, a hierarchical multi-game framework is developed: the distribution network operator (DSO), as the leader of the stackelberg game, formulates dynamic electricity prices; the virtual power plants and the virtual power plants and electric vehicle aggregators (EVAs) realize power trading and cost sharing based on cooperative game; EV users dynamically select electric vehicle aggregators with differentiated service packages through evolutionary game. The bisection method combined with the alternating direction multiplier method (ADMM) is used to solve the problem, and the example is used to verify that the proposed model can effectively consider the actual situation of users and meet the diversified charging needs of users. At the same time, the model can coordinate the interests of multiple parties and reduce the operating costs of various entities.