Volume 41 Issue 4
Aug.  2023
Turn off MathJax
Article Contents
Article Navigation >  Journal of Transport Information and Safety  > 2023  >  41(4): 154-162
LIANG Lu, HAN Fei. A Site Selection Model for Electric Vehicle Charging Stations Considering Queuing Time and Charging Cost[J]. Journal of Transport Information and Safety, 2023, 41(4): 154-162. doi: 10.3963/j.jssn.1674-4861.2023.04.016
Citation: LIANG Lu, HAN Fei. A Site Selection Model for Electric Vehicle Charging Stations Considering Queuing Time and Charging Cost[J]. Journal of Transport Information and Safety, 2023, 41(4): 154-162. doi: 10.3963/j.jssn.1674-4861.2023.04.016
shu

A Site Selection Model for Electric Vehicle Charging Stations Considering Queuing Time and Charging Cost

doi: 10.3963/j.jssn.1674-4861.2023.04.016

  • College of Transport Engineering, Chang'an University, Xi'an 710064, China

  • Received Date: 2023-01-18
    Available Online: 2023-11-23
    Abstract
  • A reasonable layout of electric vehicle charging stations plays a crucial role in reducing range anxiety, improving travel comfort, and promoting the adoption of electric vehicles. To overcome the limitations of existing studies that overlooks the consideration of queuing time and charging cost, an improved site selection model for charging stations is established with the objectives of minimizing range anxiety and charging costs. This model explicitly considers queueing and detouring behaviors in charging. The characteristics of charging behavior of electric vehicles are analyzed, and a distance constraint for allowable path deviations is introduced to establish a limit on detour distances in charging paths, thereby reducing the scale of the set of deviation paths in the road network. The characteristics of the charging station queueing system are analyzed, and an analytical expression for the average queueing time of the system is derived with constraints such as acceptable queueing time threshold and budget cost. Considering the patterns of range anxiety and the stepped electricity pricing, a site selection model for charging stations is proposed to minimize range anxiety and charging costs, and the Lingo software is used to solve the model. A case study is conducted on a partial road network in the city of Xi'an. The results show that based on the proposed model, a total queue time and a total charging cost are 5.84 h and 1 440 Yuan, respectively. Compared to the model without considering queue time and charging costs, the system queue time and the total charging cost are decreased by 1.19 h and 240 Yuan, respectively. An Analysis of the charging station budget cost B shows that when B ≤ 500 million Yuan, the total range anxiety and charging costs decrease as B increases. However, when B > 500 million Yuan, further increase in B does not result in further reduction of total range anxiety and charging costs. Under the conditions of budget costs B = 300 million, 400 million, and 500 million Yuan, respectively, the impact of path deviation distance η on the optimization objective is analyzed. As the path deviation distance η increases from 0 km to 4 km, the total range anxiety and charging costs show a decreasing trend.

     

    • FullText(HTML)
  • loading
    • References(25)
  • [1]
    GONG L L, CAO W, LIU K L, et al. Optimal charging strategy for electric vehicles in residential charging station under dynamic spike pricing policy[J]. Sustainable Cities and Society, 2020, 63: 104-124.
    [2]
    OUYANG X, XU M, ZHOU B J. An Elastic demand model for locating electric vehicle charging stations[J]. Networks and Spatial Economics, 2022, 22(1): 1-31. doi: 10.1007/s11067-021-09546-5
    [3]
    ZHANG Y, ZHANG Q, FARNOOSH A, et al. GIS-based multi-objective particle swarm optimization of charging stations for electric vehicles[J]. Energy, 2019, 169: 844-853. doi: 10.1016/j.energy.2018.12.062
    [4]
    TAO Y, HUANG M H, CHEN Y P, et al. Review of optimized layout of electric vehicle charging infrastructures[J]. Journal of Central South University, 2021, 28 (10): 3268-3278. doi: 10.1007/s11771-021-4842-3
    [5]
    LIN W T, HUA G W. The flow capturing location model and algorithm of electric vehicle charging stations[C]. International Conference on Logistics, Informatics and Service Sciences, Beijing: Beijing Jiaotong University, 2015.
    [6]
    XIAO S Q, LEI X, HUANG T, et al. Coordinated planning for fast charging stations and distribution networks based on an improved flow capture location model[J]. CSEE Journal of Power and Energy Systems, 2023, 9(4): 1505-1516.
    [7]
    KIM J G, KUBY M. The deviation-flow refueling location model for optimizing a network of refueling stations[J]. International Journal of Hydrogen Energy, 2012, 37(6): 5406-5420. doi: 10.1016/j.ijhydene.2011.08.108
    [8]
    OUYANG X, XU M, ZHOU B J. An elastic demand model for locating electric vehicle charging stations[J]. Networks & Spatial Economics, 2022, 22(1): 1-31.
    [9]
    WU Z, ZHUANG Y, ZHOU S, et al. Bi-level planning of multi-functional vehicle charging stations considering land use types[J]. Energies, 2020, 13(5): 1283-1301. doi: 10.3390/en13051283
    [10]
    GUO F, YANG J, LU J Y. The battery charging station location problem: Impact of users' range anxiety and distance convenience[J]. Transportation Research Part E: Logistics & Transportation, 2018, 114: 1-18.
    [11]
    XU M, MENG Q. Optimal deployment of charging stations considering path deviation and nonlinear elastic demand[J]. Transportation Research Part B: Methodological, 2020, 135: 120-142. doi: 10.1016/j.trb.2020.03.001
    [12]
    张智禹, 王致杰, 杨皖昊, 等. 基于充电需求预测的电动汽车充电站选址规划研究[J]. 电测与仪表, 2023, 4(20): 1-19. https://www.cnki.net/KCMS/detail/detail.aspx?dbcode=IPFD&filename=ZGGS202306002010&dbname=IPFDLAST2023

    ZHANG Z Y, WANG Z J, YANG W H, et al. Research on location planning of electric vehicle charging station based on charging demand prediction[J]. Electrical Measurement & Instrumentation, 2023, 4(20): 1-19. (in Chinese) https://www.cnki.net/KCMS/detail/detail.aspx?dbcode=IPFD&filename=ZGGS202306002010&dbname=IPFDLAST2023
    [13]
    XIAO D, AN S, CAI H, et al. An optimization model for electric vehicle charging infrastructure planning considering queuing behavior with finite queue length[J]. The Journal of Energy Storage, 2020, 29: 101317. doi: 10.1016/j.est.2020.101317
    [14]
    SHAHRAKI N, CAI H, TURKAY M, et al. Optimal locations of electric public charging stations using real world vehicle travel patterns[J]. Transportation Research Part D: Transport and Environment, 2015, 41: 165-176. doi: 10.1016/j.trd.2015.09.011
    [15]
    HUANG Y, KOCKELMAN K M. Electric vehicle charging station locations: Elastic demand, station congestion, and network equilibrium[J]. Transportation Research Part D: Transport and Environment, 2020, 78: 102-118.
    [16]
    CHEN T D, KOCKELMAN K M, KHAN M. Locating electric vehicle charging stations: Parking-based assignment method for Seattle, Washington[J]. Transportation Research Record, 2018, 2385(1): 28-36.
    [17]
    罗思杰, 邹复民, 郭峰, 等. 基于轨迹数据的出租车充电站选址方法[J]. 计算机工程与应用, 2022, 58(8): 273-282. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202208029.htm

    LUO S J, ZOU F M, GUO F, et al. Taxi charging station location method based on trajectory data[J]. Computer Engineering and Applications, 2022, 58(8): 273-282. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202208029.htm
    [18]
    GENG L, LU Z, GUO X, et al. Coordinated operation of coupled transportation and power distribution systems considering stochastic routing behaviour of electric vehicles and prediction error of travel demand[J]. IET Generation, Transmission & Distribution, 2021, 15(14): 2112-2116.
    [19]
    ZHAO Y Q, GUO Y, GUO Q L, et al. Deployment of the electric vehicle charging station considering existing competitors[J]. IEEE Transactions on Smart Grid, 2020, 11(5): 4236−4248. doi: 10.1109/TSG.2020.2991232
    [20]
    XU M, YANG H, WANG S A. Mitigate the range anxiety: Siting battery charging stations for electric vehicle drivers[J]. Transportation Research Part C: Emerging Technologies, 2020, 114(2): 164-188.
    [21]
    黄柳, 胡丹丹. 考虑路径偏差和里程焦虑下充/换电站联合布局定容优化[J]. 物流技术, 2021, 40(6): 68-75. https://www.cnki.com.cn/Article/CJFDTOTAL-WLJS202106012.htm

    HUANG L, HU D D. Constant capacity optimization of joint layout of charging/changing station considering path deviation and mileage anxiety[J]. Logistics Technology, 2021, 40(6): 68-75. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WLJS202106012.htm
    [22]
    邵赛, 关伟, 毕军. 考虑排队时间和里程约束的竞争充电站选址问题[J]. 交通运输系统工程与信息, 2016, 16(6): 169-175. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201606026.htm

    SHAO S, GUAN W, BI J. Competitive charging station location problem considering queuing time and mileage constraints[J]. Transportation System Engineering and Information, 2016, 16(6): 169-175. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201606026.htm
    [23]
    胡诚, 黄合来, 李欣彤, 等. 考虑心理潜变量的城市电动自行车用户出行决策行为[J]. 交通信息与安全, 2021, 39(3): 111-120. doi: 10.3963/j.jssn.1674-4861.2021.03.014

    HU C, HUANG H L, LI X T, et al. Travel decision-making behavior of urban electric bicycle users considering psychological latent variables[J]. Journal of Transport Information and Safety, 2019, 39(3): 111-120. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2021.03.014
    [24]
    武渊, 叶宁. 城市路网中电动汽车充电站双层多目标选址定容模型[J]. 山西大学学报(自然科学版), 2021, 44(4): 695-704. https://www.cnki.com.cn/Article/CJFDTOTAL-SXDR202104009.htm

    WU Y, YE N. Two-layer multiobjective siting capacity model of electric vehicle charging stations in urban road network[J]. Journal of Shanxi University(Natural Science Edition), 2021, 44(4): 695-704. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SXDR202104009.htm
    [25]
    AGRAWAL A, BARRATT S, BOYD S. Learning convex optimization models[J]. IEEE/CAA Journal of Automatica Sinica, 2021, 8(8): 1355-1364.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(5)  / Tables(6)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (293) PDF downloads(18) Cited by()
    Proportional views
    Related

    Copyright Editorial Office of Transport Information and Safety鄂ICP备05003336号-2

    Address：No. 1178，Heping Avenue, Wuchang, Wuhan, CHINA (430063)

    Tel：027-86580355 Email：jtjsj@vip.163.com

    Supported by: Beijing Renhe Information Technology Co. Ltd  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return