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

[thumbnail of Wang-Infield-IJEPES2018-Markov-Chain-Monte-Carlo-simulation-of-electric-vehicle]
Preview
 Text. Filename: Wang_Infield_IJEPES2018_Markov_Chain_Monte_Carlo_simulation_of_electric_vehicle.pdf
Accepted Author Manuscript
License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 logo
Download (1MB)| 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.

CORE (COnnecting REpositories)