文章摘要
李宏仲,强伟,高宇男,等.考虑用户出行特性和配电网线路可用裕度的充电站规划[J].电力系统自动化,2018,42(23):48-56. DOI: 10.7500/AEPS20170730004.
LI Hongzhong,QIANG Wei,GAO Yunan, et al.Charging Station Planning Considering Users' Travel Characteristics and Line Availability Margin of Distribution Network[J].Automation of Electric Power Systems,2018,42(23):48-56. DOI: 10.7500/AEPS20170730004.
考虑用户出行特性和配电网线路可用裕度的充电站规划
Charging Station Planning Considering Users' Travel Characteristics and Line Availability Margin of Distribution Network
DOI:10.7500/AEPS20170730004
关键词: 电动汽车用户  电动汽车充电站  配电网  出行特性  候选站址选择  可用裕度
KeyWords: electric vehicle user  electric vehicle charging station  distribution network  travel characteristic  candidate site selection  availability margin
上网日期:2018-10-19
基金项目:国家自然科学基金资助项目(51777126)
作者单位E-mail
李宏仲 上海电力学院电气工程学院, 上海市 200090  
强伟 上海电力学院电气工程学院, 上海市 200090 gsrwei@163.com 
高宇男 上海电力学院电气工程学院, 上海市 200090  
孙伟卿 上海理工大学光电信息与计算机工程学院, 上海市 200093  
摘要:
      考虑到电动汽车用户、电动汽车充电站和配电网三者之间的相互影响关系,根据路网交通流量和用户出行特性建立了电动汽车用户的年总耗时成本模型。在计及电动汽车充电站和配电网的年总成本的基础上建立了全社会年总成本模型,以此对电动汽车充电站进行优化规划。针对电动汽车充电站接入配电网的馈线布局,考虑了线路的通道资源问题,并建立了可用裕度模型。根据环境条件、社会条件、自然条件等外在条件对充电站的候选站址进行初步筛选。然后,以单位时间内充电站的综合成本最小为目标对充电站的容量进行优化配置。利用离散二进制粒子群算法和删除路径算法实现了电动汽车充电站的选址定容及接入配电网的馈线规划。最后,以33节点的路网和19节点的配电网为例,验证了所提模型及求解方法的合理性和有效性。
Abstract:
      Considering the interactions among electric vehicle users, electric vehicle charging stations and distribution network, the annual total time cost model of electric vehicle users is developed based on the traffic flow of the related road network and users' travel characteristics. Considering the total annual cost of electric vehicle charging stations and distribution networks, the total annual cost model of the whole society is established to optimize the layout of electric vehicle charging stations. The model of availability margin for the channel resources is introduced, which is applied in the process of planning the feeder layout of electric vehicle charging stations connected to the distribution network. Secondly, the external conditions such as environmental, social and natural requirements are taken into account to preliminarily screen the candidate sites of charging stations. Then, the capacity of the charging station is scheduled with the aim of minimizing the comprehensive cost of the charging station in the unit time. The discrete binary particle swarm algorithm and the deleting path algorithm are used to determine the locations and capacity of electric vehicle charging stations and draw up the feeder layout of electric vehicle charging stations connected to distribution network, respectively. Finally, a 33-bus road network and a 19-bus distribution network are taken as examples to verify the effectiveness and practicability of the proposed planning model.
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