Distribution Feeder Reconfiguration with Distributed Generation Using Backward/Forward Sweep Power Flow – Grey Wolf Optimizer

Syed Muhammad Fadli Syed Drus, N. M. Saad, M. Abas, S. Ab-Ghani, N. Jaalam, Abid Ali
{"title":"Distribution Feeder Reconfiguration with Distributed Generation Using Backward/Forward Sweep Power Flow – Grey Wolf Optimizer","authors":"Syed Muhammad Fadli Syed Drus, N. M. Saad, M. Abas, S. Ab-Ghani, N. Jaalam, Abid Ali","doi":"10.1109/CSPA57446.2023.10087738","DOIUrl":null,"url":null,"abstract":"This article presents an effective combination method based on Backward/Forward Sweep Power Flow- Grey Wolf optimizer (BFSPF-GWO) for feeder reconfiguration in a distribution network with the presence of distributed generation (DG). The 33-bus test system by adding five tie line switches is proposed with the objective functions of minimizing total power losses and improving the voltage profiles. The results reveal a reduction in active and reactive power losses at 71.41% and 67.66%, respectively. The optimal sizing of DG and installation location are identified by installing a 2.26 MW DG at bus 29. The magnitudes of voltage profiles and critical buses in the test system have been improved. The proposed BFSPF-GWO algorithm’s performance in DG placement and sizing with feeder reconfiguration has been evaluated by comparing the results with Mixed-integer optimization by GA (MIOGA) and Particle Swarm optimization (PSO).","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA57446.2023.10087738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This article presents an effective combination method based on Backward/Forward Sweep Power Flow- Grey Wolf optimizer (BFSPF-GWO) for feeder reconfiguration in a distribution network with the presence of distributed generation (DG). The 33-bus test system by adding five tie line switches is proposed with the objective functions of minimizing total power losses and improving the voltage profiles. The results reveal a reduction in active and reactive power losses at 71.41% and 67.66%, respectively. The optimal sizing of DG and installation location are identified by installing a 2.26 MW DG at bus 29. The magnitudes of voltage profiles and critical buses in the test system have been improved. The proposed BFSPF-GWO algorithm’s performance in DG placement and sizing with feeder reconfiguration has been evaluated by comparing the results with Mixed-integer optimization by GA (MIOGA) and Particle Swarm optimization (PSO).
使用向后/向前扫描功率流的分布式发电配电馈线重新配置-灰狼优化器
提出了一种基于后向/前向扫描潮流-灰狼优化器(BFSPF-GWO)的配电网馈线重构方法。提出了一种增加5个并线开关的33母线测试系统,其目标是减小总功耗和改善电压分布。结果表明,有功和无功损耗分别降低了71.41%和67.66%。通过在29总线上安装2.26 MW的DG,确定了DG的最佳尺寸和安装位置。改进了测试系统中电压分布和关键母线的大小。通过与遗传算法(MIOGA)和粒子群算法(PSO)的混合整数优化结果比较,评价了BFSPF-GWO算法在馈线重新配置下DG放置和尺寸的性能。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书