Optimal Integration of Electric Vehicle Charging Stations and Compensating Photovoltaic Systems in a Distribution Network Segregated into Communities

Willy Stephen Tounsi Fokui, L. Ngoo, Michael Juma Saulo
{"title":"Optimal Integration of Electric Vehicle Charging Stations and Compensating Photovoltaic Systems in a Distribution Network Segregated into Communities","authors":"Willy Stephen Tounsi Fokui, L. Ngoo, Michael Juma Saulo","doi":"10.55579/jaec.202264.380","DOIUrl":null,"url":null,"abstract":"This paper proposes a method of optimally utilizing electric vehicles (EVs) in the distribution network. The method is firstly based on segregating the distribution network into communities and then optimally placing an EV charging station (EVCS) in each community using the backward forward sweep (BFS) technique. The Second phase uses particle swarm optimization (PSO) to size and allocates photovoltaic systems in the network for power loss minimization and voltage improvement. The proposed method is tested on an IEEE 33 node test feeder and simulation results showed the effectiveness of the BFS in finding the best nodes for the placement of EVCS in each community as well as the effectiveness of the PSO in allocating the photovoltaic systems. To validate the effectiveness of the BFS technique, its results obtained are compared with those obtained when the EVCSs are placed on some nodes other than those chosen by the BFS technique.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Adv. Eng. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55579/jaec.202264.380","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper proposes a method of optimally utilizing electric vehicles (EVs) in the distribution network. The method is firstly based on segregating the distribution network into communities and then optimally placing an EV charging station (EVCS) in each community using the backward forward sweep (BFS) technique. The Second phase uses particle swarm optimization (PSO) to size and allocates photovoltaic systems in the network for power loss minimization and voltage improvement. The proposed method is tested on an IEEE 33 node test feeder and simulation results showed the effectiveness of the BFS in finding the best nodes for the placement of EVCS in each community as well as the effectiveness of the PSO in allocating the photovoltaic systems. To validate the effectiveness of the BFS technique, its results obtained are compared with those obtained when the EVCSs are placed on some nodes other than those chosen by the BFS technique.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
社区配电网中电动汽车充电站与补偿光伏系统的优化集成
本文提出了配电网中电动汽车的优化利用方法。该方法首先将配电网划分为多个社区,然后采用后向扫描(BFS)技术在每个社区中最优设置电动汽车充电站。第二阶段采用粒子群优化(PSO)对电网中的光伏系统进行尺寸和分配,以实现功率损耗最小化和电压改善。在IEEE 33节点测试馈线上对该方法进行了测试,仿真结果表明BFS在寻找EVCS在每个社区中的最佳节点以及PSO在光伏系统分配方面的有效性。为了验证BFS技术的有效性,将其结果与将evcs放置在非BFS技术选择的节点上的结果进行了比较。这是一篇在知识共享署名许可(http://creativecommons.org/licenses/by/4.0/)条款下发布的开放获取文章,该许可允许在任何媒介上不受限制地使用、分发和复制,只要原始作品被适当引用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Incremental Ensemble Learning Model for Imbalanced Data: a Case Study of Credit Scoring Comparing the Performance of Molecular Docking Tools for HIV-1 Protease Inhibitors Determinants of Net Interest Margin in Commercial Banks in Viet Nam Development of a Laboratory-Scale Steam Boiler for Polyurethane (Foam) Waste Recycling Machine Development of Decentralized Speed Controllers for a Differential Drive Wheel Mobile Robot
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1