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电动汽车充电设施分层递进式定址定容最优规划
引用本文:孙 元,丁茂生,柳劲松,杨永标,许晓慧,徐青山,时姗姗.电动汽车充电设施分层递进式定址定容最优规划[J].电测与仪表,2014,51(11):1-6.
作者姓名:孙 元  丁茂生  柳劲松  杨永标  许晓慧  徐青山  时姗姗
作者单位:东南大学伺服控制技术教育部工程研究中心;国网宁夏电力公司;国网上海市电力公司电力科学研究院;南京南瑞集团公司;中国电力科学研究院;
基金项目:国家能源应用技术研究及工程示范项目(NY20110702-1);国家科技支撑计划项目(2013BAA01B00);国家自然科学基金项目(51361130152)
摘    要:电动汽车充电设施作为发展电动汽车产业的重要配套基础设施,是电动汽车产业推广与普及的前提。文章采用分层递进式方法对充电设施进行定址定容规划建模求解。首先,根据交通、地理、需求等因素,采用层次分析法来确定充电设施的候选站址;然后,建立以总体建设成本最小为目标,以充电需求和线路传输容量为约束的优化模型,采用遗传算法,对候选站址进行优化,得到充电设施的建设地址和容量。最后通过一个充电设施规划算例,建立最优化模型并予以求解,验证本文所给的充电设施规划方法的合理性和可行性。

关 键 词:电动汽车  充电设施  最优规划  遗传算法
收稿时间:2013/11/26 0:00:00
修稿时间:2013/11/26 0:00:00

Optimal Planning Considering Capacity and Site of EV Charging Facility by Progression
Sun Yuan,Ding Maosheng,LIU Jian-song,Yang Yongbiao,Xu Xiaohui,Xu Qingshan and SHI Shanshan.Optimal Planning Considering Capacity and Site of EV Charging Facility by Progression[J].Electrical Measurement & Instrumentation,2014,51(11):1-6.
Authors:Sun Yuan  Ding Maosheng  LIU Jian-song  Yang Yongbiao  Xu Xiaohui  Xu Qingshan and SHI Shanshan
Affiliation:Engineering Research Centre of Motion Control,Ministry of Education,Southeast University,Ningxia Electric Power Corp,Shanghai Electric Power Corp. Electric Power Research Institute,Nanjing Nari Group Corporation,China Electric Power Research Institute, Haidian District, Beijing 210061, China,Engineering Research Centre of Motion Control,Ministry of Education,Southeast University,Shanghai Electric Power Corp. Electric Power Research Institute
Abstract:As an important supporting infrastructure for the development of electric vehicle industry, Electric vehicle charging facilities are the prerequisite of the promotion and popularization of electric vehicle industry. This paper makes a model for the EV charging facilities planning and solves it. We make the model in two steps. Firstly, we use the Analytical Hierarchy Process to find the candidate sites of the charging facilities, according to the factors of transportation, geography, demand and others. Secondly, we optimize the candidate sites of the charging facilities. We make a model which objective is the smallest overall construction cost and constraints are the charging demand and the transmission capacity of the power lines. At the end, we give a hypothetical example of the charging facilities planning to further elaborate the model and to verify the rationality and feasibility of the model and the method.
Keywords:Electric  Vehicles  Charging  Facilities  Optimal  Planning  Genetic  Algorithm
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