Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (5): 1471-1477.doi: 10.13229/j.cnki.jdxbgxb20181270

Previous Articles    

Location and capacity model of electric vehicle charging station considering commuting demand

Qing-yu LUO(),Wan-li TIAN,Hong-fei JIA()   

  1. College of Transportation, Jilin University, Changchun 130022, China
  • Received:2018-12-24 Online:2019-09-01 Published:2019-09-11
  • Contact: Hong-fei JIA E-mail:luoqy@jlu.edu.cn;jiahf@jlu.edu.cn

RICH HTML

 20   

PDF (PC)

331

Abstract:

In order to meet the charging demand of electric vehicle for commute users near their workplace, a charging station location and capacity model is constructed. The objectives are to minimize the cost of building charging station and minimize the generalized charging cost of users. The convenience factor is introduced to quantify the charging expectation of the user to obtain the number of electric vehicles and the power demand of the charging station. The calculation example shows that the location of charging station is not sensitive to the threshold of convenience coefficient, but the economy of construction becomes worse with the decrease in the threshold of convenience coefficient. Therefore, the range of the threshold value of convenience coefficient under different programming objectives is suggested.

Key words: transportation planning and management, location and capacity determination of charging station, elastic demand analysis, charging cost, convenience coefficient

CLC Number: 

  • U491

Fig.1

Research area and alternative sites"

Table 1

Number of electric vehicles and construction costs of chargers at each alternative site"

地点电动汽车数量/辆单位快充建设成本/元单位慢充建设成本/元
总计3 782--
144011 7003 900
243211 5003 700
342511 4003 600
440911 1303 500
541411 7003 900
644711 5003 700
742011 2003 300
847111 4003 600
941411 9004 100

Table 2

Costs of auxiliary equipment and power of chargers"

设备等级辅助设备成本/元充电设备效率/kw每小时充电增加的公里数/(km·h-1)
慢充30 0001510
快充100 0009080

Table 3

Distribution of specific gravity and driving mileage and charging times for each level of electric vehicles"

组别所占比重/%单程行驶里程/km慢充充电时间/h快充充电时间/h
1291~100.70.26
22211~201.70.39
31721~302.70.51
41031~403.70.64
5741~504.70.76
6551~605.70.89
7361~706.71.01
88>708.71.26

Table 4

Parameter values of users’ generalized"

参 数数值参 数数值
WB/元9 000TW/h8
WD/天251Vw/(km·h-1)4

Table 5

Values of relevant parameters in model"

参数数值参数数值
K1Y/年5
Gj1ω10.5
TD/km1ω20.5
R/km0.5

Fig.2

Location of charging stations and service scope"

Table 6

Number of chargers and construction costs"

阈值站点快充数量慢充数量建设费用/元
12118221 568 400
5131241 756 300
785171 138 100
1027211998 700
593111 261 000
76114859 400
202598838 100
57291 007 500
76114859 400
∞2330479 500
5390556 300
7180301 600

Fig.3

Total cost at four different thresholds"

Fig.4

Amount of energy demand and number of electric vehicles served at four different thresholds"

1 DongJ, LinZ. Within-day recharge of plug-in hybrid electric vehicles: energy impact of public charging infrastructure[J]. Transportation Research Part D: Transport and Environment, 2012, 17(5): 405-412.
2 NieY, GhamamiM, ZockaieA, et al. Optimization of incentive polices for plug-in electric vehicles[J]. Transportation Research Part B: Methodological, 2016, 84: 103-123.
3 NieY, GhamamiM. A corridor-centric approach to planning electric vehicle charging infrastructure[J]. Transportation Research Part B: Methodological, 2013, 57: 172-190.
4 HeF, YinY, ZhouJ. Deploying public charging stations for electric vehicles on urban road networks[J]. Transportation Research Part C: Emerging Technologies, 2015, 60: 227-240.
5 程宏波, 肖永乐, 王勋, 等. 基于引力模型的电动汽车充电站选址规划[J]. 电工电能新技术, 2016, 35(5): 61-66.
ChengHong-bo, XiaoYong-le, WangXun, et al. Site planning of electric vehicles charging station based on gravity model[J]. Advanced Technology of Electrical Engineering & Energy, 2016, 35(5): 61-66.
6 HuangY, ZhouY. An optimization framework for workplace charging strategies[J]. Transportation Research Part C: Emerging Technologies, 2015, 52: 144-155.
7 ZhuZ H, GaoZ Y, ZhengJ F, et al. Charging station location problem of plug-in electric vehicles[J]. Journal of Transport Geography, 2016, 52: 11-22.
8 YangY, YaoE, YangZ, et al. Modeling the charging and route choice behavior of BEV drivers[J]. Transportation Research Part C: Emerging Technologies, 2016, 65: 190-204.
9 SunX, YamamotoT, MorikawaT. Charge timing choice behavior of battery electric vehicle users[J]. Transportation Research Part D: Transport and Environment, 2015, 37: 97-107.
10 DongJ, LiuC, LinZ. Charging infrastructure planning for promoting battery electric vehicles: an activity-based approach using multiday travel data[J]. Transportation Research Part C: Emerging Technologies, 2014, 38: 44-55.
11 PearreN S, KemptonW, GuenslerR L, et al. Electric vehicles: how much range is required for a day’s driving[J]. Transportation Research Part C: Emerging Technologies, 2011, 19(6): 1171-1184.
[1] CAO Qian, LI Jun, LIU Yu, QU Da-wei. Construction of driving cycle based on Markov chain for passenger car in Changchun City [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1366-1373.
[2] SUN Bao-feng, GAO Kun, SHEN Xiu-xiu, LIANG Ting. Location model of gas station for network expansion based on capacity balance and variable coverage radius [J]. 吉林大学学报(工学版), 2018, 48(3): 704-711.
[3] XU Liang,CHENG Guo-zhu. Setting minimum vehicle speed limit on freeway based on speed scattering and economic speed [J]. 吉林大学学报(工学版), 2010, 40(03): 661-0665.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd