Stochastic collaborative planning method for electric vehicle charging stations

Shu Wang, Ke Meng, Fengji Luo, Zhao Xu, Yu Zheng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

Abstract

Electric vehicles (EV) is a promising solution for reducing the environment adverse effect of road transport. In this study, a multi-objective, multi-stage collaborative planning model is proposed for the integrated EV charging stations and power distribution network. The proposed model aims to minimize the investment & operation costs of the distribution system and maximize the annually captured traffic flow. The uncertainties for both slow charging load and fast charging load are considered. The MOEA/D algorithm is employed to find the Pareto frontier of the proposed model. Simulations based on a case study of a 54-node distribution system and a 25-node traffic network system proves the effectiveness of proposed method.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
PublisherIEEE
Pages503-508
Number of pages6
ISBN (Electronic)9781509040759
DOIs
Publication statusPublished - 8 Dec 2016
Event7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 - Sydney, Australia
Duration: 6 Nov 20169 Nov 2016

Conference

Conference7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
CountryAustralia
CitySydney
Period6/11/169/11/16

Keywords

  • charging station
  • distribution system planning
  • Electric vehicle
  • multi-objective optimization
  • vehicle-to-grid

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Control and Optimization
  • Signal Processing

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