Electric vehicle capacity forecasting model with application to load levelling

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)
107 Downloads (Pure)

Abstract

There are many uncertainties in forecasting the charging and discharging capacity required by electric vehicles (EVs) often as a consequence of stochastic usage and intermittent travel. In terms of large-scale EV integration in future power networks this paper develops a capacity forecasting model which considers eight particular uncertainties in three categories. Using the model, a typical application of EVs to load levelling is presented and exemplified using a UK 2020 case study. The results presented in this paper demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale EV integration.
Original languageEnglish
Title of host publication2015 IEEE Power & Energy Society General Meeting: Proceedings
DOIs
Publication statusPublished - 05 Oct 2015
EventIEEE Power & Energy Society General Meeting - Colorado, Denver, United States
Duration: 27 Jul 201531 Jul 2015
http://www.pes-gm.org/2015/

Publication series

Name2015 IEEE Power & Energy Society General Meeting: Proceedings
PublisherIEEE
ISSN (Print)1932-5517

Conference

ConferenceIEEE Power & Energy Society General Meeting
CountryUnited States
CityDenver
Period27/07/201531/07/2015
Internet address

Keywords

  • electric vehicle (EV), capacity forecasting, uncertainty analysis, load levelling

Fingerprint Dive into the research topics of 'Electric vehicle capacity forecasting model with application to load levelling'. Together they form a unique fingerprint.

  • Cite this

    Zhou, B., Littler, T., & Foley, A. (2015). Electric vehicle capacity forecasting model with application to load levelling. In 2015 IEEE Power & Energy Society General Meeting: Proceedings (2015 IEEE Power & Energy Society General Meeting: Proceedings). https://doi.org/10.1109/PESGM.2015.7285829