Electric Vehicle Load Control Strategy Based on Improved Aquila Optimizer Algorithm

• Published in: 2023 6th Asia Conference on Energy and Electrical Engineering (ACEEE) pp. 372 - 376
• Main Authors: Meng, Zijie, Jin, Xin, Liu, Jiale, Cai, Xinlei, Zhu, Jinzhou, Pan, Tingzhe
• Format: Conference Proceeding
• Language: English
• Published: IEEE 21.07.2023
• Subjects: Aquila optimizer algorithm; Behavioral sciences; Electric potential; electric vehicle; Electric vehicle charging; Linear programming; load regulation; operation; optimization; Power grids; Regulation; Voltage control
• DOI: 10.1109/ACEEE58657.2023.10239561

The accurate and reasonable charging/discharging strategy of electric vehicles plays an important role in power grid regulation. In this paper, a charging/discharging model of electric vehicles is constructed, which fully considers the impact of large-scale charging on the power grid. Secondly, the optimal objective function with the best economy is proposed. The improved Aquila algorithm is used to solve the objective function, and the optimal charging/discharging control strategy is obtained. Finally, the load control strategy of the electric vehicle is verified by a simulation example. In the calculation, different operating conditions are considered, and the comparative calculation results of different operating conditions shows that the optimization control strategy proposed in this paper not only improves voltage stability, but also significantly reduces the cost of charging and discharging after optimization, improves the economic efficiency of electric vehicle charging and discharge, and slightly reduces the impact on grid operation.