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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Electrical Power & Energy Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
