A methodology for optimisation of power system demand due to EV charging load

Peng Zhang, Kejun Qian, Chengke Zhou, Brian G. Stewart, Donald M. Hepburn

Research output: Contribution to journalArticle

162 Citations (Scopus)

Abstract

This paper presents a methodology of optimizing power systems demand due to electric vehicle (EV) charging load. Following a brief introduction to the charging characteristics of EV batteries, a statistical model is presented for predicting the EV charging load. The optimization problem is then described, and the solution is provided based on the model. An example study is carried out with error and sensitivity analysis to validate the proposed method. Four scenarios of various combinations of EV penetration levels and charging modes are considered in the study. A series of numerical solutions to the optimization problem in these scenarios are obtained by serial quadratic programming. The results show that EV charging load has significant potential to improve the daily load profile of power systems if the charging loads are optimally distributed. It is demonstrated that flattened load profiles may be achieved at all EV penetration levels if the EVs are charged through a fast charging mode. In addition, the implementation of the proposed optimization is discussed with analyses on the impact of travel pattern and the willingness of customers.
Original languageEnglish
Pages (from-to)1628-1636
Number of pages9
JournalIEEE Transactions on Power Systems
Volume27
Issue number3
DOIs
Publication statusPublished - 1 Aug 2012

Keywords

  • power system
  • load demand
  • electric vehicle
  • quadratic programming

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