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电动汽车用户对充电设施的需求呈现高度异质化特征，构建集成慢充、快充和超快充的多类型充电设施体系成为必然趋势。为此，提出一种考虑用户充电行为决策的多类型充电设施协同优化规划方法。首先，采用蒙特卡罗抽样与起讫点分析法模拟不同用户的交通行为，结合目的地充电与应急充电场景，分析用户在不同类型设施中的选择行为，进而建立电动汽车多类型充电需求预测模型；然后，综合考虑站内不同类型充电设施的功率差异、成本差异及其相互影响，以年化的充电站建设成本、运维成本和用户寻站成本综合最小为目标，构建集成多类型设施的充电站协同规划模型。最后，基于某城市区域开展算例验证，与仅含单一快充设施的规划方案相比，多类型充电设施协同规划能使总成本降低8.26%，充电设施利用率提升19.27%，用户需求满足度提高18.03%。
Abstract：The demand for charging facilities from electric vehicle(EV)users shows a highly heterogeneous feature,and building a system for multi-type charging facilities which integrates slow,fast and ultra-fast charging has become an inevitable trend. Aimed at this issue,a collaborative optimization planning method for multi-type charging facilities considering users' charging behavior decisions is proposed. First,Monte Carlo sampling and the Origin-Destination analysis method are adopted to simulate the traffic behaviors of different users. Combined with the destination charging and emergency charging scenarios,the choice behaviors of users in different types of facilities are analyzed,and a multitype charging demand prediction model for EV is further established. Then,with the comprehensive consideration of power differences,cost differences and their mutual influences among different types of charging facilities within a charging station,the minimization of annualized construction cost,operation and maintenance cost and user search cost of the charging station is taken as the objective,and a collaborative planning model for the charging station integrating multi-type facilities is constructed. Finally,a case study of one certain urban area is conducted for verification. It is found that compared with the planning scheme that only includes fast charging facilities,the collaborative planning for multi-type charging facilities can reduce the total cost by 8.26%,increase the utilization rate of charging facilities by19.27%,and improve the satisfaction degree of users' demand by 18.03%.
[1]中华人民共和国公安部.全国机动车保有量达4. 53亿辆驾驶人达5. 42亿人[EB/OL].(2025-01-18). https：//www. mps. gov. cn/n2254314/n6409334/c9939035/content.html,2025.
[2]Lee Jae Hyun,Chakraborty D,Hardman S J,et al. Exploring electric vehicle charging patterns:Mixed usage of charging infrastructure[J]. Transportation Research Part D:Transport and Environment,2020,79:102249.
[3]侯慧，唐俊一，王逸凡，等（Hou Hui,Tang Junyi,Wang Yifan,et al）.城区电动汽车充电站布局规划研究（Layout planning of electric vehicle charging stations in urban areas）[J].电力系统保护与控制（Power System Protection and Control）,2022,50(14):181-187.
[4]Kapoor A,Patel V S,Sharma A,et al. Optimal planning of fast EV charging stations in a coupled transportation and electrical power distribution network[J]. IEEE Transactions on Automation Science and Engineering,2024,21(3):4261-4271.
[5]严干贵，刘华南，韩凝晖，等（Yan Gangui,Liu Huanan,Han Ninghui,et al）.计及电动汽车时空分布状态的充电站选址定容优化方法（An optimization method for location and capacity determination of charging stations considering spatial and temporal distribution of electric vehicles）[J].中国电机工程学报（Proceedings of the CSEE）,2021,41(18):6271-6283.
[6]肖白，高峰（Xiao Bai,Gao Feng）.含不同容量充电桩的电动汽车充电站选址定容优化方法（Optimization method of electric vehicle charging stations'site selection and capacity determination considering charging piles with different capacities）[J].电力自动化设备（Electric Power Automation Equipment）,2022,42(10):157-166.
[7]Luo Lizi,Gu Wei,Zhou Suyang,et al. Optimal planning of electric vehicle charging stations comprising multi-types of charging facilities[J]. Applied Energy,2018,226:1087-1099.
[8]程杉，王豪杰，徐其平，等（Cheng Shan,Wang Haojie,Xu Qiping,et al）.含超大功率充电的多类型充电设施两阶段选址定容方法（Two-stage siting and capacity determination method for multi-type charging facilities with ultrahigh-power charging）[J].电力系统保护与控制（Power System Protection and Control）,2024,52(23):33-44.
[9]Zhang Hongcai,Hu Zechun,Xu Zhiwei,et al. An integrated planning framework for different types of PEV charging facilities in urban area[J]. IEEE Transactions on Smart Grid,2016,7(5):2273-2284.
[10]王震坡，梁兆文，等.中国新能源汽车大数据研究报告-2023[M]. 4版.北京：机械工业出版社，2023.
[11]Martin W A,McGuckin N A. Travel estimation techniques for urban planning[Z]. Washington DC:Transport Research Board National Research Council,1998.
[12]Sarmiento-Delgado F,Clairand J M,Guerra-Teran P,et al.Electric vehicle charging load prediction for private cars and taxis based on vehicle usage data[C]//IEEE CHILEAN Conference on Electrical,Electronics Engineering,Information and Communication Technologies. Valparaiso,Chile,2019.
[13]中国电动汽车充电基础设施促进联盟.中国电动汽车用户充电行为研究报告（2022）[M].北京：机械工业出版社，2022.
[14]邵尹池，穆云飞，余晓丹，等（Shao Yinchi,Mu Yunfei,Yu Xiaodan,et al）.“车–路–网”模式下电动汽车充电负荷时空预测及其对配电网潮流的影响（A spatial-temporal charging load forecast and impact analysis method for distribution network using EVs-traffic-distribution model）[J].中国电机工程学报（Proceedings of the CSEE）,2017,37(18):5207-5219.
[15]李娜，吴凯萍（Li Na,Wu Kaiping）.基于POI数据的城市功能区识别与分布特征研究（A POI data-based study of identification and distribution characteristics of urban functional districts）[J].遥感技术与应用（Remote Sensing Technology and Application）,2022,37(6):1482-1491.
[16]张美霞，徐立成，杨秀，等（Zhang Meixia,Xu Licheng,Yang Xiu,et al）.基于电动汽车充电需求时空分布特性的充电站规划研究（Planning of charging stations based on spatial and temporal distribution characteristics of electric vehicle charging demand）[J].电网技术（Power System Technology）,2023,47(1):256-265.
[17]柯玮文，吴升，柯日宏（Ke Weiwen,Wu Sheng,Ke Rihong）.基于OD流向语义和时空语义聚类的居民出行特征分析方法（A method for analyzing residents’travel characteristics based on OD flow semantics and spatiotemporal semantic clustering）[J].地球信息科学学报（Journal of Geo-Information Science）,2023,25(11):2150-2163.
[18]肖志国（Xiao Zhiguo）.区域OD矩阵反推技术评价及其理论研究（Study on Evaluation and Theory of Regional OD Matrix Estimation）[D].武汉：华中科技大学（Wuhan:Huazhong University of Science and Technology）,2006..
[19]刘珏，穆云飞，董晓红，等（Liu Jue,Mu Yunfei,Dong Xiaohong,et al）.考虑交通时滞的配电-交通耦合系统协同优化运行策略（Collaborative operation strategy for power-traffic coupling system considering traffic）[J].电力系统及其自动化学报（Proceedings of the CSU-EPSA）,2024,36(10):49-59.
[20]Shao Chengcheng,Qian Tao,Wang Yanan,et al. Coordinated planning of extreme fast charging stations and power distribution networks considering on-site storage[J].IEEE Transactions on Intelligent Transportation Systems,2021,22(1):493-504.
[21]赵书强，周靖仁，李志伟，等（Zhao Shuqiang,Zhou Jingren,Li Zhiwei,et al）.基于出行链理论的电动汽车充电需求分析方法（EV charging demand analysis based on trip chain theory）[J].电力自动化设备（Electric Power Automation Equipment）,2017,37(8):105-112.——
[22]齐彤岩，刘冬梅，刘莹（Qi Tongyan,Liu Dongmei,Liu Ying）.北京市居民出行时间成本研究（A study of the traveling time cost of Beijing residents）[J].公路交通科技（Journal of Highway and Transportation Research and Development）,2008,25(6):144-146,153.
[23]He Kecheng,Jia Hongjie,Mu Yunfei,et al. Coordinated planning of fixed and mobile charging facilities for electric vehicles on highways[J]. IEEE Transactions on Intelligent Transportation Systems,2023,24(9):10087-10098.
[24]Li Qifeng,Ayyanar R,Vittal V. Convex optimization for DES planning and operation in radial distribution systems with high penetration of photovoltaic resources[J]. IEEE Transactions on Sustainable Energy,2016,7(3):985-995.
[25]南琦琦，穆云飞，董晓红，等（Nan Qiqi,Mu Yunfei,Dong Xiaohong,et al）.电动汽车快速充电网综合评估指标体系与方法（Comprehensive evaluation index system and method for fast charging network of electric vehicles）[J].电力系统自动化（Automation of Electric Power Systems）,2020,44(1):83-91.
基本信息:
DOI：10.19635/j.cnki.csu-epsa.001699
中图分类号:U491.8;TM910.6
引用信息:
[1]陆鑫,穆云飞,郝璐,等.考虑用户充电行为决策的多类型充电设施协同优化规划方法[J].电力系统及其自动化学报,2025,37(12):1-14.DOI:10.19635/j.cnki.csu-epsa.001699.
基金信息:
国家电网公司科学技术项目（5400-202312220A-1-1-ZN）