考虑负荷时空分布的电动汽车充电站优化配置

Optimal Configuration of Electric Vehicle Charging Stations Considering Load Spatiotemporal Distribution

针对电动汽车快充负荷和充电资源错配的问题,运用蒙特卡洛法预测充电站配置变化下的负荷分布,以社会总成本最小化为目标,充分考虑充电站、用户、电网和交通等多方利益,构建了一种新的充电站优化模型,并使用改进的多染色体遗传算法进行求解,得到了适用于区域充电站的规划方案。以上海市浦东新区为例进行算例仿真研究,验证了所提方法的有效性,为解决电动汽车快充负荷与充电资源错配问题提供了有力的决策支持。

Regarding the problem of mismatch between fast charging load and charging resources for electric vehicles,an innovative optimization model for charging stations is developed by applying Monte Carlo simulation to predict the load distribution under different configurations of charging stations.The model aimes to minimize the overall social cost while considering the interests of charging stations,users,power grid,and transportation.An improved multi-chromosome genetic algorithm is employed to solve the optimization problem and obtain optimal planning solutions for charging stations in the region.The effectiveness of the proposed approach is validated using the case of Pudong New Area in Shanghai.The research findings provide strong decision support for addressing the mismatch issue between fast charging load and charging resources for electric vehicles.