电工技术学报  2017, Vol. 32 Issue (增刊2): 190-202    DOI: 10.19595/j.cnki.1000-6753.tces.L70051
电力系统及其自动化 |
基于电动汽车出行随机模拟的充电桩需求研究
麻秀范, 李颖, 王皓, 王超, 洪潇
华北电力大学电气与电力工程学院 北京 102206。
Research on Demand of Charging Piles Based on Stochastic Simulation of EV Trip Chain
Ma Xiufan, Li Ying, Wang Hao, Wang Chao, Hong Xiao
School of Electrical & Electronic Engineering North China Electric Power University Beijing 102206 China
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摘要 提出基于电动汽车出行随机模拟的充电桩需求分析方法。该方法通过对电动汽车在各地点停车时长的相似性分析,将不同地点归类为六类充电功能区域,考虑用户对电池荷电状态变化的接受范围,建立电动汽车出行及充电模型,运用蒙特卡洛随机模拟电动汽车一日出行链和在各目的地的充电需求,模拟中考虑各区域停车数随时间的变化和充电同时性,在模型中输入电动汽车模拟量和各类型电动汽车比例,可得到各区域总的充电桩与停车位的比例(桩位比)和快慢速充电桩的比例。模拟结果显示,工作区桩位比并不高,全天中三次及以上行程目的地内的桩位比较大;快慢充比例较大的区域一般为停车时长较短而充电需求较大的区域,居住区也有快充需求;当电动汽车数量不变时,随着车辆最大续驶里程的增大,桩位比并无明显变化规律,快慢充比例逐渐减小。
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麻秀范
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洪潇
关键词 电动汽车出行链随机模拟充电桩需求    
Abstract:A method is put forward in this paper to analyze the demand of EV charging piles based on stochastic simulation. Six charging areas are built by correlation analysis of parking time in different places, drivers’ acceptance range of battery state of charge are considered, and EV’ s traveling and charging model is established, where Monte Carlo method is used to stimulate EVs’ daily trip chain and charging demand in each destination. Meanwhile, the variation of parking number and the simultaneity of charging number are recorded. The proportion of total charging piles with parking space and the proportion of fast and slow piles are available in each area when entering the scale and proportion of EVs. It is proved that, the proportion of charging piles is not that high in working area, while the one is higher in three or more trip destinations. The proportion of fast and slow piles is higher in the areas with short parking time and urgent charging demand, while there exist fast charging demand in residential area. With constant EV scale and the increase of maximum driving range, there is no obvious change in the proportion of total charging piles, but the proportion of fast and slow piles goes down.
Key wordsElectric vehicle    trip chain    stochastic simulation    demand of charging piles   
收稿日期: 2016-08-21      出版日期: 2017-11-14
PACS: TM910.6  
  U469.72  
作者简介: 麻秀范 女,1970年生,博士,副教授,研究方向为配网规划与运行,电动汽车规划与运行。E-mail: xfmhbdll@vip.sina.com。
引用本文:   
麻秀范, 李颖, 王皓, 王超, 洪潇. 基于电动汽车出行随机模拟的充电桩需求研究[J]. 电工技术学报, 2017, 32(增刊2): 190-202. Ma Xiufan, Li Ying, Wang Hao, Wang Chao, Hong Xiao. Research on Demand of Charging Piles Based on Stochastic Simulation of EV Trip Chain. Transactions of China Electrotechnical Society, 2017, 32(增刊2): 190-202.
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