引用本文:刘东林,王育飞,张宇,薛花,米阳,于艾清.基于Huff模型的电动汽车充电站选址定容方法[J].电力自动化设备,2023,43(11):103-110
LIU Donglin,WANG Yufei,ZHANG Yu,XUE Hua,MI Yang,YU Aiqing.Siting and sizing method of electric vehicle charging stations based on Huff model[J].Electric Power Automation Equipment,2023,43(11):103-110
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基于Huff模型的电动汽车充电站选址定容方法
刘东林1, 王育飞1, 张宇1,2, 薛花1, 米阳1, 于艾清1
1.上海电力大学 电气工程学院,上海 200090;2.国网上海市电力公司电力科学研究院,上海 200437
摘要:
对于用户充电选择行为随机性的欠考虑,导致充电站服务范围划分和容量配置不合理的问题,提出了一种基于Huff模型的电动汽车充电站选址定容方法。综合考虑充电站规模、充电价格、用户充电成本对用户充电选择行为的影响,利用Huff模型分析用户对不同充电站的选择概率,并基于用户的选择概率确定充电站的服务范围和充电需求;综合考虑用户充电可达性、规划区域总功率、电动汽车充电功率,以充电站年总成本最小为目标,建立充电站的选址定容模型,并采用免疫克隆选择-变邻域搜索混合算法求解模型。MATLAB仿真结果表明所提选址定容方法能合理地划分服务范围,提高充电站规划的经济性。
关键词:  电动汽车  充电站  Huff模型  服务范围  免疫克隆选择算法  充电随机性
DOI:10.16081/j.epae.202304013
分类号:U469.72
基金项目:国家自然科学基金资助项目(61873159);上海市科技创新行动计划项目(22010501400)
Siting and sizing method of electric vehicle charging stations based on Huff model
LIU Donglin1, WANG Yufei1, ZHANG Yu1,2, XUE Hua1, MI Yang1, YU Aiqing1
1.College of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China;2.Electric Power Research Institute of State Grid Shanghai Municipal Electric Power Company, Shanghai 200437, China
Abstract:
In order to solve the problem of unreasonable service range division and capacity allocation of charging stations due to the lack of consideration of the randomness of users’ charging selection behavior, a siting and sizing method of electric vehicle charging stations based on Huff model is proposed. Based on the comprehensive consideration of the influence of charging station scale, charging price and users’ charging cost on users’ charging selection behavior, the Huff model is used to analyze users’ selection probabilities of different charging stations, and the service range and charging demand of charging stations are determined based on the users’ selection probabilities. Considering the users’ charging accessibility, the total power of planning area and the charging power of electric vehicles comprehensively, the siting and sizing model of charging stations is established with the goal of minimizing the total annual cost of charging stations, which is solved by the immune clonal selection-variable neighborhood search hybrid algorithm. MATLAB-based simulative results show that the proposed siting and sizing method can reasonably divide the service range and improve the economy of charging station planning.
Key words:  electric vehicles  charging station  Huff model  service range  immune clonal selection algorithm  charging randomness

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