Robust Distributed Generation Investment Accommodating Electric Vehicle Charging in a Distribution Network

Jian Zhao, Zhao Xu, Jianhui Wang, Cheng Wang, Jiayong Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)


Distributed generation (DG) can locally provide energies in distribution network and thus help to reduce the negative impact caused by large-scale electric vehicle (EV) charging demand. This paper proposes a two-stage robust DG investment planning model capable of accommodating uncertainty of EV charging demand and renewable generations. The DG investment location and size are optimized in the first stage and the distribution network operation feasibility in the worst case scenario is checked in the second stage to avoid constraint violations. The EV charging demand uncertainty is modeled by sampling from real-life scenarios of travel behavior. Finally, the column-and-constraint generation algorithm is adopted to solve the proposed problem. Simulations on modified IEEE 123-node distribution network demonstrate the effectiveness of the proposed model.

Original languageEnglish
Article number8267098
Pages (from-to)4654-4666
Number of pages13
JournalIEEE Transactions on Power Systems
Issue number5
Publication statusPublished - 1 Sep 2018


  • charging demand
  • distributed generation
  • Distributed power generation
  • Distribution network
  • electric vehicle
  • Electric vehicle charging
  • Investment
  • Planning
  • robust optimization
  • Robustness
  • Uncertainty
  • Wind power generation

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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