Online intelligent demand management of plug-in electric vehicles in future smart parking lots

Elham Akhavan-Rezai, Mostafa F. Shaaban, E. F. El-Saadany, Fakhri Karray

Research output: Contribution to journalArticlepeer-review

94 Scopus citations

Abstract

This paper proposes an online intelligent demand coordination of plug-in electric vehicles (PEVs) in distribution systems. The proposed method is based on the assignment of scores to PEVs through a fuzzy expert system. As well, without violation of grid operational constraints, the PEVs are optimally charged in order to maximize the owners' satisfaction in terms of the energy delivered. The optimization problem of online PEV charging is defined as mixed-integer nonlinear programming. Simulation on a typical distribution network proves the effectiveness of the proposed methodology. Results of the analysis indicate that for more critical PEVs, which have shorter parking duration and higher required charging time, the proposed solution outperforms in more robust energy delivery to the PEV and, accordingly, more satisfaction for the owner.

Original languageBritish English
Article number7078950
Pages (from-to)483-494
Number of pages12
JournalIEEE Systems Journal
Volume10
Issue number2
DOIs
StatePublished - Jun 2016

Keywords

  • Decision making
  • distribution systems
  • electric vehicles
  • energy management
  • expert systems
  • fuzzy logic
  • priority-based charge coordination
  • smart parking lots

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