Consider the Collaborative Optimization Strategy of Electric Vehicles Under Dynamic Electricity Price Mechanism

Driven by the sustainable development strategy of ‘’dual carbon’’, the consumption situation of renewable energy in China is worrying, and it is urgent to need more flexible control resources to adjust Power system networks. To some extent, electric vehicles can interact with the power system network in both directions. When the electric vehicle is not in the driving state, it can transmit excess electrical energy back to the grid, thus playing the role of an energy storage device; And when an electric car needs to be charged, it can take power from the grid to charge it. A large number of electric vehicles continue to be put into market use, and if their charging behavior is not properly guided, it will cause a huge impact on the power system network. Therefore, the focus of this paper is to use the electricity price elasticity matrix to guide the charging behavior of users, It reduces the impact on the power system network, standardizes the charging behavior of electric vehicle users, and ensures high utilization of renewable energy To achieve the maximization of bilateral benefits for both the grid and users in the optimization process, it shows that under the consideration of multiple interests The most effective scheduling method is to adopt the collaborative optimization strategy.