考虑驾驶人出行链的电动汽车充电站规划  

Planning for Charging Stations of Electric Vehicles Considering Drivers' Trip Chains

作　　者：王冬[1] 刘继春[1] 曹芷健 牛毅[1] 唐虎[1] 刘俊勇[1] WANG Dong;LIU Jiehun;CAO Zhijian;NIU Yi;TANG Hu;LIU Junyong(College of Electrical Engineering and Infomlation Technology,Siehuan University,Chengdu 610065,China)

机构地区：[1]四川大学电气信息学院,成都610065

出　　处：《电力系统及其自动化学报》2018年第6期1-9,52,共10页Proceedings of the CSU-EPSA

基　　金：国家自然科学基金资助项目(51377111)

摘　　要：基于出行链和Dijkstra最短路径算法,本文提出了考虑驾驶人出行链的充电站选址定容模型。通过各类出行链的出行产生量,分析不同时段下居民区、工作区、商业区的车辆数变化特性,通过蒙特卡洛抽样法模拟不同时空分布下电动汽车的出行行为和充电行为。将电网收益以及用户的平均充电距离作为目标函数,提出了计及目标优先级的模糊双目标优化方法,并运用粒子群优化算法对模型进行求解。最后通过算例分析表明所提模型具有一定的可行性和合理性。Based on travel chains and Dijkstra＇s shortest-path algorithm,a locating and sizing model for charging stations is proposed considering drivers＇ trip chains. Through the generation of various trip chains,the changing characteristics of vehicle numbers in different time intervals and different areas（i.e.,residential,industrial,and business）areanalyzed. The travelling and charging behaviors of electric vehicles in different temporal and spatial distributions aresimulated using Monte Carlo sampling technique. A fuzzy biobjective optimization approach that considers the objective priority is presented with the grid revenue and the average travel distance of charging users as objective functions.To solve this model,particle swarm optimization algorithm is used. Finally,the analysis of a numerical example verifiesthe feasibility and rationality of the proposed model.

关 键 词：电动汽车 选址定容 蒙特卡洛 出行链 最优路径 粒子群优化算法 

分 类 号：TM615[电气工程—电力系统及自动化]