Robust Planning of Electric Vehicle Charging Facilities with an Advanced Evaluation Method

Guibin Wang, Xian Zhang, Huaizhi Wang, Jian Chun Peng, Hui Jiang, Yitao Liu, Chao Wu, Zhao Xu, Wenxin Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

36 Citations (Scopus)


The planning of charging facilities (CFs) for electric vehicles (EVs) plays an important role for the extensive applications of EVs. Uncertainties existing in the development of future EV technology should be properly modeled to ensure the robustness of the planning scheme. The uncertainties concerned include EV development types, growth rate of load and traffic flow, and distributions of load and traffic flow in the smart grid. The existing single-stage planning model cannot fully evaluate the risks brought by all kinds of uncertainties. Given this background, the multistage CF planning problem considering uncertainties is studied in this work. First, several typical uncertainties in future smart grid with a high penetration of EVs are considered to generate development scenarios for multistage planning. Then, the well-established data envelopment analysis is utilized to evaluate the planning schemes while the novel EV expected energy not supplied cost is defined to measure the service ability of CFs. The final planning result obtained by the proposed framework will not only have good performance in the current stage but also exhibit robustness for all the considered scenarios in the future stage with respect to uncertainties. The application potential of the designed multistage planning framework is proved by an example with both the distribution network and traffic network included.
Original languageEnglish
Pages (from-to)866-876
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Issue number3
Publication statusPublished - 1 Mar 2018


  • Data envelopment analysis (DEA)
  • electric vehicle (EV)
  • multistage charging facility (CF) planning
  • uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


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