文章摘要
贾龙,胡泽春,宋永华,等.高速路网上电动汽车充电站布点优化[J].电力系统自动化,2015,39(15):82-89. DOI: 10.7500/AEPS20140528007.
JIA Long,HU Zechun,SONG Yonghua, et al.Planning of Electric Vehicle Charging Stations in Highway Network[J].Automation of Electric Power Systems,2015,39(15):82-89. DOI: 10.7500/AEPS20140528007.
高速路网上电动汽车充电站布点优化
Planning of Electric Vehicle Charging Stations in Highway Network
DOI:10.7500/AEPS20140528007
关键词: 电动汽车  高速路网  荷电状态  充电需求  充电站布点优化
KeyWords: electric vehicle  highway network  state-of-charge  charging demand  charging station planning
上网日期:2015-07-28
基金项目:国家高技术研究发展计划(863计划)资助项目(2012AA050211);国家自然科学基金资助项目(51261130473)
作者单位E-mail
贾龙 清华大学电机工程与应用电子技术系, 北京市 100084
电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084 
jia l07@mails.tsinghua.edu.cn 
胡泽春 清华大学电机工程与应用电子技术系, 北京市 100084
电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084 
 
宋永华 清华大学电机工程与应用电子技术系, 北京市 100084
电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084 
 
占恺峤 清华大学电机工程与应用电子技术系, 北京市 100084
电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084 
 
丁华杰 清华大学电机工程与应用电子技术系, 北京市 100084
电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084 
 
摘要:
      电动汽车的发展需要合理规划的充电站与之匹配,高速路网上的充电站是电动汽车在城市间远距离行驶的保证。研究了电动汽车在高速路网中的充电需求分布,采用两阶段法确定充电站规划方案。考虑充电站距高速公路出入口的距离和续航里程确定候选站址;考虑充电需求,最小化建站成本、接电网成本和运维成本,确定最优建站位置和容量。在包含6个出入口、4个交叉路口的算例系统中选出90个候选站址,规划得到24座充电站。采用的方法可以满足目标,并随初始电池荷电状态期望、站间影响因数和建站数量约束变化而得到不同的规划方案。
Abstract:
      The rapid development of electric vehicles (EVs) requires the appropriate planning of EV charging stations. EV charging stations in a highway network are the guarantee for long distance driving. This paper studies the charging demand distribution in highway network and proposes a planning scheme by the two-step method. The first step is to determine the candidate stations considering the distance from highway entrance/exit to charging stations and EV mileage. The second step is to determine the optimal location and capacity of EV charging stations considering the charging demand, minimal construction cost, grid connection cost, operation and maintenance cost. A highway network containing six gateways and four intersections is proposed to select 90 candidate stations and build 24 optimal charging stations. The method proposed in this paper is able to meet all the objectives and the planning scheme varies with the state-of-charge expectation, and affecting factors between stations and quantity constraint of stations. This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2012AA050211) and National Natural Science Foundation of China (No. 51261130473).
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