Research on the Control Method of Electric Vehicle Charging, Discharging, and Storage Integrated Station for Diversified Vehicle-Grid Interaction

With the rapid increase in the number of electric vehicles, the interaction between electric vehicles and the power grid has become a core issue in modern energy management. This paper proposes an optimized control strategy for an electric vehicle charging, discharging, and storage integrated station aimed at diversified vehicle-grid interaction. The strategy comprehensively considers the charging, discharging, and energy storage needs of electric vehicles and designs an efficient control model based on genetic algorithms, simulated annealing algorithms, and neural network technologies. Through multi-scenario simulation analysis, the effectiveness and feasibility of the proposed method in improving charging and storage efficiency, balancing loads, and enhancing system robustness are verified. This research not only provides theoretical support for the collaborative management of electric vehicles and the power grid but also lays the foundation for the future development of smart grids.