Research on Electric Vehicle Charging and Discharging Optimization Strategy Based on Multi-Strategy Integrated Zebra Optimization Algorithm

Under the background of dual-carbon target, electric vehicle (EV) industry has been developing rapidly and become the main force to promote green transportation. However, as the number of EV s continues to increase, when EV s are connected to the power grid in a large-scale disorder, it will make the grid load appear “peak on peak” phenomenon, resulting in grid load fluctuations. In order to realize the “peak shaving and valley filling” of the grid load and ensure the stability of the grid, this paper studies the charging and discharging behaviors of EV s in Vehicle-to-Grid (V2G) mode, and proposes a Multi-strategy Integrated Zebra Optimization Algorithm (MIZOA). MIZOA for solving the charging and discharging coordination problem of EVs after large-scale access to the grid. Considering the charging and discharging time, characteristics and user cost of EVs, the MIZOA algorithm is combined with the ordered charging and discharging strategy through the V2G model for experimental verification. The experimental results show that the application of MIZOA to the ordered charging and discharging strategy reduces the peak-to-valley different rate by 7.03% compared to ordered charging and 18.87% compared to disordered charging. The experimental results show that the combination of the MIZOA algorithm with the EV ordered charging and discharging strategy can effectively reduce the fluctuation of the power grid load, and play the role of “peak shaving and valley filling” for the power grid load while reducing the charging cost of the users.