姚明, 毛文杰, 曹淑超, 笪丹宁. 基于多源数据的电动汽车充电设施布局优化方法研究[J]. 智慧电力, 2023, 51(9): 31-37.
引用本文: 姚明, 毛文杰, 曹淑超, 笪丹宁. 基于多源数据的电动汽车充电设施布局优化方法研究[J]. 智慧电力, 2023, 51(9): 31-37.
YAO Ming, MAO Wen-jie, CAO Shu-chao, DA Dan-ning. Optimization Method of Electric Vehicle Charging Facility Layout Based on Multi-source Data[J]. Smart Power, 2023, 51(9): 31-37.
Citation: YAO Ming, MAO Wen-jie, CAO Shu-chao, DA Dan-ning. Optimization Method of Electric Vehicle Charging Facility Layout Based on Multi-source Data[J]. Smart Power, 2023, 51(9): 31-37.

基于多源数据的电动汽车充电设施布局优化方法研究

Optimization Method of Electric Vehicle Charging Facility Layout Based on Multi-source Data

  • 摘要: 针对电动汽车充电设施布局与电动汽车用户需求平衡性问题,提出了一种基于多源数据的电动汽车充电设施布局优化方法。首先,基于兴趣点位置、用户产生充电需求时的地点、需求偏好等多源数据构建电动汽车充电站双层布局优化模型。上层模型以社会总成本为目标函数对电动汽车充电站进行选址定容优化;下层模型以寻址距离、寻址时间、拥挤程度3个指标搭建用户最佳选择模型;然后,利用遗传算法对双层规划模型进行求解,获得电动汽车充电站布局优化方案。最后,通过实例验证了所提方法的可行性。

     

    Abstract: Aiming at the problem of balancing the layout of electric vehicle charging facilities with the demand of electric vehicle users,an electric vehicle charging facility layout optimization method based on multi-source data is proposed. Firstly,the two-layer layout optimization model is set up for EV charging stations based on multi-source data such as POI(Point of interesting)location,location and demand preference of users when they generate charging demand. The upper model takes the total social cost as the objective function to optimize the location and capacity of EV charging stations;the lower model builds the user’s best choice model based on three indexes,i.e. addressing distance,addressing time and congestion level;Then,the two-layer planning model is solved by genetic algorithm to obtain the layout optimization scheme of EV charging stations. Finally,the feasibility of the proposed method is illustrated by example verification.

     

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