Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/109613
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical and Electronic Engineering | - |
dc.creator | Hungbo, M | - |
dc.creator | Gu, M | - |
dc.creator | Meegahapola, L | - |
dc.creator | Littler, T | - |
dc.creator | Bu, S | - |
dc.date.accessioned | 2024-11-08T06:10:28Z | - |
dc.date.available | 2024-11-08T06:10:28Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/109613 | - |
dc.language.iso | en | en_US |
dc.publisher | The Institution of Engineering and Technology | en_US |
dc.rights | © 2023 The Authors. IET Smart Grid published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. | en_US |
dc.rights | This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. | en_US |
dc.rights | The following publication Hungbo, M., et al.: Impact of electric vehicles on low-voltage residential distribution networks: a probabilistic analysis. IET Smart Grid. 6(5), 536–548 (2023) is available at https://doi.org/10.1049/stg2.12123. | en_US |
dc.subject | Distribution network | en_US |
dc.subject | Electric vehicle | en_US |
dc.subject | Electric vehicle charging | en_US |
dc.subject | Probabilistic analysis | en_US |
dc.subject | Solar power stations | en_US |
dc.subject | Vehicle-to-grid (V2G) | en_US |
dc.subject | Volt-varcontrol | en_US |
dc.subject | Voltage control | en_US |
dc.subject | Voltage unbalance | en_US |
dc.title | Impact of electric vehicles on low-voltage residential distribution networks : a probabilistic analysis | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 536 | - |
dc.identifier.epage | 548 | - |
dc.identifier.volume | 6 | - |
dc.identifier.issue | 5 | - |
dc.identifier.doi | 10.1049/stg2.12123 | - |
dcterms.abstract | The past two decades have seen a rapid increase in electric vehicles (EVs) for several reasons, such as policy directives to reduce carbon emissions in the transport sector and technology advancements in the EV industry. However, this has increased the load demand on the power grid, especially in the low-voltage (LV) network, as most EVs are charged at EV owner premises. This paper investigates the impact of EVs on the LV residential distribution network using a probabilistic modelling framework. Probability distribution functions for EV charging power are derived using the United Kingdom (UK) EV dataset. The study has investigated multiple EV penetration levels, different probability distribution functions for EV charging representation, vehicle-to-grid (V2G), solar photovoltaic (PV) generation, and the volt-var capability of the solar-PV inverter. The results have shown that as EV penetration increases in the distribution network, there is a significant increase in transformer loading and a decrease in the steady-state voltage levels. V2G has positively impacted the distribution network. A case study carried out on a real LV feeder with solar-PV generation has shown how PV generation and volt-var functionality of the PV inverter help reduce the impact of EV charging and V2G. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IET smart grid, Oct. 2023, v. 6, no. 5, p. 536-548 | - |
dcterms.isPartOf | IET smart grid | - |
dcterms.issued | 2023-10 | - |
dc.identifier.scopus | 2-s2.0-85166907968 | - |
dc.identifier.eissn | 2515-2947 | - |
dc.description.validate | 202411 bcch | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Hungbo_Impact_Electric_Vehicles.pdf | 2.19 MB | Adobe PDF | View/Open |
Page views
5
Citations as of Nov 17, 2024
Downloads
7
Citations as of Nov 17, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.