基于排队模型的大型园区充电站负载能力研究  

Research on capacity of electric vehicle charging station in large industrial park based on queuing model

作　　者：李西园[1,2] 封宝华 尚永红[1] 孙雪吟[1] 解峥 陈时雨[1] LI Xiyuan;FENG Baohua;SHANG Yonghong;SUN Xueyin;XIE Zheng;CHEN Shiyu(Beijing Institute of Spacecraft Environment Engineering,Beijing 100094,China;School of Aeronautic Science and Engineering,Beihang University,Beijing 100191,China)

机构地区：[1]北京卫星环境工程研究所,北京100094 [2]北京航空航天大学航空科学与工程学院,北京100191

出　　处：《应用科技》2019年第6期10-15,共6页Applied Science and Technology

摘　　要：电动汽车充电桩的建设是制约着电动车日常使用的关键问题之一。同时,大量电动汽车在高峰时间充电亦会对电网带来较大负荷,需要在规划阶段对充电站进行优化,降低对电网的压力。以某大型工业园区充电站为对象,统计了用户在充电周期、充电量、充电时间上的习惯,分析结果显示该充电站用户到达间隔近似服从负指数分布,充电服务时间近似服从Gamma分布。基于M/G/k排队模型,建立了该园区内部充电桩的排队仿真模型,通过蒙特卡洛方法给出了不同时段充电站的排队长度、排队时间等参数,并对比了充电服务时间分布不同对排队模型关键参数的影响,为未来纯电动汽车充电桩的建设与优化具有直观的参考意义。The construction of charging stations is one of the main factors restricting daily use of EVs. Meanwhile, a large number of EVs charging at peak time will also bring huge load to the grid. It is necessary to optimize the charging stations in the planning stage to reduce the pressure on the grid. Taking a large industrial park charging station as an object, this paper counts the users ’ habits in aspects of charging period, charging quantity and charging time. The analysis results show that the user arrival interval approximately obeys the exponential distribution, and the service time approximately obeys the Gamma distribution. A queuing simulation model of charging stations in a large industrial park was established based on the M/G/k queuing model. The queuing length, queuing time and other parameters of charging stations in different periods of time were given by Monte Carlo method, and the influence of different distribution of service time on key parameters of queuing model was compared, which provides a reference for construction and optimization of charging stations of EVs in future.

关 键 词：电动汽车 充电站 负载 优化 排队模型 蒙特卡洛法 仿真 M/G/k 

分 类 号：TM721[电气工程—电力系统及自动化]