Forecast of urban EV charging load and smart control concerning uncertainties

Xiaolin Wang, Yongquan Nie, K. W.E. Cheng, Jie Mei

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

3 Citations (Scopus)

Abstract

Popularizing electric vehicles (EV) can be one of the most effective ways to deal with the ever severe air pollution. However, the accumulated charging power from the increasing integration of EVs could add large pressure to the peak of power grid. In this paper, a novel EV load forecasting model is formulated based on Markov chain, allowing for the stochasticity of user behavior, traffic and weather. The impact of EV integration is assessed in a typical medium voltage (MV) system while the resulting peak load and power loss are mitigated with charging control schemes. The proposed model could help to forecast the future charging demands with probabilistic uncertainties. The smart control schemes shall instruct the aggregator to make optimal charging plan concerning security and efficiency issues.

Original languageEnglish
Title of host publication2016 International Symposium on Electrical Engineering, ISEE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509058839
DOIs
Publication statusPublished - 7 Feb 2017
Event2016 International Symposium on Electrical Engineering, ISEE 2016 - Hong Kong, Hong Kong
Duration: 14 Dec 2016 → …

Publication series

Name2016 International Symposium on Electrical Engineering, ISEE 2016

Conference

Conference2016 International Symposium on Electrical Engineering, ISEE 2016
Country/TerritoryHong Kong
CityHong Kong
Period14/12/16 → …

Keywords

  • Electric vehicle
  • Markov chain
  • Smart charging
  • user behavior

ASJC Scopus subject areas

  • Control and Optimization
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

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