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

Wang, Yue and Infield, David (2018) Markov Chain Monte Carlo simulation of electric vehicle use for network integration studies. International Journal of Electrical Power and Energy Systems, 99. pp. 85-94. ISSN 0142-0615

[img]
Preview
Text (© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/)
Manuscript File.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview

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.

Item Type: Article
Additional Information: Department of Engineering & Applied Design
Uncontrolled Keywords: Electric vehicles, Markov Chain, Monte Carlo, multi-place charging, uncertainty.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Related URLs:
Depositing User: Yue Wang
Date Deposited: 25 Oct 2019 09:24
Last Modified: 19 May 2020 14:23
URI: http://eprints.chi.ac.uk/id/eprint/4909

Actions (login required)

View Item View Item