Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80871
Title: The prediction of electric vehicles load profiles considering stochastic charging and discharging behavior and their impact assessment on a real UK distribution network
Authors: Hu, Q 
Li, H
Bu, S 
Keywords: Distribution network
Electric Vehicles (EVs)
Impact assessment
Monte Carlo simulation
Issue Date: 2019
Publisher: Elsevier
Source: Energy procedia, 2019, v. 158, p. 6458-6465 How to cite?
Journal: Energy procedia 
Abstract: Electric vehicle (EV) as one of the most promising solutions to reduce the greenhouse emission is developing faster than ever. With the increasing number of EVs, the additional load will cause technical issues on the existing distribution network. To cope with possible challenges, the reasonable prediction of EV load profile is fundamental to the evaluation of how the distribution network responds to the potential increasing EV penetration. This paper investigates the critical issues that EVs bring into the network at various penetration levels considering the uncertainties due to stochastic charging and discharging behaviour. To deal with these uncertainties, a Monte Carlo based simulation method is utilised to create EV charging and discharging profiles. Three scenarios are proposed and their impacts on a real UK distribution network are analysed by the simulation in OpenDSS and MATLAB. The simulation results imply that EV charging process has the negative effect in regard to thermal stress, voltage drop, system efficiency and power factor of the network. Conclusions are drawn to provide the guidance for the upgrading and reinforcement of the existing network assets.
Description: 10th International Conference on Applied Energy, ICAE 2018, Hong Kong, 22-25 August 2018
URI: http://hdl.handle.net/10397/80871
EISSN: 1876-6102
DOI: 10.1016/j.egypro.2019.01.134
Rights: © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy.
The following publication Hu, Q., Li, H., & Bu, S. (2019). The Prediction of Electric Vehicles Load Profiles Considering Stochastic Charging and Discharging Behavior and Their Impact Assessment on a Real UK Distribution Network. Energy Procedia, 158, 6458-6465 is available at https://doi.org/10.1016/j.egypro.2019.01.134
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