Charging pricing strategy for community electric vehicles based on evolutionary game

The load of the smart grid includes traditional load and active load. The active load on the distribution network side in China is mainly composed of electric vehicles. One of its important characteristics is that power demand changes with electricity prices. With the popularity of electric vehicles, agent is set to play a significant role in the charging management of electric vehicles within the community. Formulating the pricing and power purchase strategies of agents in such a way that a win-win situation for agents and electric vehicle owners can be achieved has become an important research topic. For the above reasons, a pricing and power purchase strategy for community agents is proposed. The pursuit of maximizing interests by agents and vehicle owners is modeled as an evolutionary game. The MILP method is used to transform the nonlinear constraints therein into linear constraints. Finally, a practical example is used to illustrate the basic characteristics of the proposed method and verify the effectiveness and feasibility of the proposed scheduling optimization method. Eventually, the globally optimal pricing strategy was obtained.