Markov Chain Monte Carlo simulation of electric vehicle use for network integration studies

Yue Wang, David Infield

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)
56 Downloads (Pure)

Abstract

As the penetration of electric vehicles (EVs) increases, their patterns of use need to be well understood for future system planning and operating purposes. Using high resolution data, accurate driving patterns were generated by a Markov Chain Monte Carlo (MCMC) simulation. The simulated driving patterns were then used to undertake an uncertainty analysis on the network impact due to EV charging. Case studies of workplace and domestic uncontrolled charging are investigated. A 99% confidence interval is adopted to represent the associated uncertainty on the following grid operational metrics: network voltage profile and line thermal performance. In the home charging example, the impact of EVs on the network is compared for weekday and weekend cases under different EV penetration levels.
Original languageEnglish
Pages (from-to)85-94
Number of pages10
JournalInternational Journal of Electrical Power and Energy Systems
Volume99
Early online date9 Jan 2018
Publication statusPublished - 31 Jul 2018

Keywords

  • electric vehicles
  • Markov Chain
  • Monte Carlo
  • multi-place charging
  • uncertainty

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