Electric Vehicle Charging Station Placement Method for Urban Areas

被引:72
作者
Cui, Qiushi [1 ]
Weng, Yang [1 ]
Tan, Chin-Woo [2 ,3 ]
机构
[1] Arizona State Univ, Dept Elect & Comp Engn, Tempe, AZ 85281 USA
[2] Stanford Univ, Stanford Smart Grid Lab, Stanford, CA 94305 USA
[3] Stanford Univ, Sustainable Syst Lab, Stanford, CA 94305 USA
基金
美国国家科学基金会;
关键词
Electric vehicle charging station; distribution grid; convexification; protective devices upgrade; DISTRIBUTION-SYSTEMS; POWER DISTRIBUTION; COST; FLOW;
D O I
10.1109/TSG.2019.2907262
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
For accommodating more electric vehicles (EVs) to battle against fossil fuel emission, the problem of charging station placement is inevitable and could be costly if done improperly. Research considers a general setup using conditions such as driving ranges for planning. However, most of the EV growths in the next decades will happen in urban areas where driving range is not the biggest concern. For such a need, we consider several practical aspects of urban systems, such as voltage regulation cost and protection device upgrade resulting from the large integration of EVs. Notably, our diversified objective can reveal the trade-off between different factors in different cities worldwide. To understand the global optimum of large-scale analysis, we studied each feature to preserve the problem convexity. Our sensitivity analysis before and after convexification shows that our approach is not only universally applicable but also has a small approximation error for prioritizing the most urgent constraint in a specific setup. Finally, numerical results demonstrate the trade-off, the relationship between different factors and the global objective, and the small approximation error. A unique observation in this paper shows the importance of incorporating the protection device upgrade in urban system planning on charging stations.
引用
收藏
页码:6552 / 6565
页数:14
相关论文
共 39 条
  • [1] Agenbroad Josh., 2014, Pulling back the veil on ev charging station costs
  • [2] [Anonymous], 2017, P 19 INT C INT SYST
  • [3] Tight-and-Cheap Conic Relaxation for the AC Optimal Power Flow Problem
    Bingane, Christian
    Anjos, Miguel E.
    Le Digabel, Sebastien
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (06) : 7181 - 7188
  • [4] Burke J. J., 1999, HARD FIND INFORM DIS
  • [5] Planning of Fast EV Charging Stations on a Round Freeway
    Dong, Xiaohong
    Mu, Yunfei
    Jia, Hongjie
    Wu, Jianzhong
    Yu, Xiaodan
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2016, 7 (04) : 1452 - 1461
  • [6] Doyle MT, 2002, 2002 IEEE POWER ENGINEERING SOCIETY SUMMER MEETING, VOLS 1-3, CONFERENCE PROCEEDINGS, P103, DOI 10.1109/PESS.2002.1043186
  • [7] Fuzzy Stochastic Programming Method: Capacitor Planning in Distribution Systems With Wind Generators
    Dukpa, Andu
    Venkatesh, B.
    Chang, Liuchen
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (04) : 1971 - 1979
  • [8] The Impact of Transport Electrification on Electrical Networks
    Dyke, Kevin J.
    Schofield, Nigel
    Barnes, Mike
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2010, 57 (12) : 3917 - 3926
  • [9] A Linear Three-Phase Load Flow for Power Distribution Systems
    Garces, Alejandro
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2016, 31 (01) : 827 - 828
  • [10] Evaluation of the Levelized Cost of Energy Method for Analyzing Renewable Energy Systems: A Case Study of System Equivalency Crossover Points Under Varying Analysis Assumptions
    Hallam, Cory R. A.
    Contreras, Carolina
    [J]. IEEE SYSTEMS JOURNAL, 2015, 9 (01): : 199 - 208