Traffic-constrained multiobjective planning of electric-vehicle charging stations

Guibin Wang, Zhao Xu, Fushuan Wen, Kit Po Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

343 Citations (Scopus)


Smart-grid development calls for effective solutions, such as electric vehicles (EVs), to meet the energy and environmental challenges. To facilitate large-scale EV applications, optimal locating and sizing of charging stations in smart grids have become essential. This paper proposes a multiobjective EV charging station planning method which can ensure charging service while reducing power losses and voltage deviations of distribution systems. A battery capacity-constrained EV flow capturing location model is proposed to maximize the EV traffic flow that can be charged given a candidate construction plan of EV charging stations. The data-envelopment analysis method is employed to obtain the final optimal solution. Subsequently, the well-established cross-entropy method is utilized to solve the planning problem. The simulation results have demonstrated the effectiveness of the proposed method based on a case study consisting of a 33-node distribution system and a 25-node traffic network system.
Original languageEnglish
Article number6555966
Pages (from-to)2363-2372
Number of pages10
JournalIEEE Transactions on Power Delivery
Issue number4
Publication statusPublished - 18 Jul 2013


  • Charging station
  • cross-entropy
  • data-envelopment analysis
  • distribution systems
  • electric vehicle (EV)
  • locating and sizing
  • traffic flow

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology


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