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文章摘要
电动汽车充电设施分层递进式定址定容最优规划
Optimal Planning Considering Capacity and Site of EV Charging Facility by Progression
Received:November 26, 2013  Revised:November 26, 2013
DOI:
中文关键词: 电动汽车、充电设施、最优规划、遗传算法
英文关键词: Electric  Vehicles,Charging  Facilities,Optimal  Planning,Genetic  Algorithm
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
Author NameAffiliationE-mail
Sun Yuan* Engineering Research Centre of Motion Control,Ministry of Education,Southeast University 220122080@seu.edu.cn 
Ding Maosheng Ningxia Electric Power Corp  
LIU Jian-song Shanghai Electric Power Corp. Electric Power Research Institute  
Yang Yongbiao Nanjing Nari Group Corporation  
Xu Xiaohui China Electric Power Research Institute, Haidian District, Beijing 210061, China  
Xu Qingshan Engineering Research Centre of Motion Control,Ministry of Education,Southeast University  
SHI Shanshan Shanghai Electric Power Corp. Electric Power Research Institute  
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中文摘要:
      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。本文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,建立最优划模型并予以求解,验证了本文所给的充电设施规划方法的合理性和可行性。
英文摘要:
      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.
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