A Novel Technique for Optimal Allocation of RDG Units on Distribution Network

Omar Muhammed Neda
{"title":"A Novel Technique for Optimal Allocation of RDG Units on Distribution Network","authors":"Omar Muhammed Neda","doi":"10.1109/icecct52121.2021.9616633","DOIUrl":null,"url":null,"abstract":"Installation of Renewable Distributed Generation (RDG) units into distribution grids are present the better solution for meeting the increasing demand for energy in the world. The RDG units are connected consumer side for ameliorating voltage profile and mitigating loss in grid. The integration of RDG units in non-proper allocation will lead to more power loss and lower voltages, leading to higher operating costs in power grids. So, RDG units should be installed at optimal bus position with proper size. In this article, a novel Dolphin Echolocation Optimization (DEO) is presented to get optimal siting and sizing of RDG units simultaneously for diminishing power loss and ameliorating profile of voltage in the grid. The ability and robustness of the DEO is checked on IEEE-33 bus. The comparison with presented Genetic Algorithm (GA) and some recent literature works is done to affirm the efficacy and superiority of DEO technique. The simulation results have shown that DEO is the finest economical algorithm for finding the optimum positioning of RDG, leading to substantial loss mitigation and boost voltage profile compared to GA and other recent works.","PeriodicalId":155129,"journal":{"name":"2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icecct52121.2021.9616633","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

Installation of Renewable Distributed Generation (RDG) units into distribution grids are present the better solution for meeting the increasing demand for energy in the world. The RDG units are connected consumer side for ameliorating voltage profile and mitigating loss in grid. The integration of RDG units in non-proper allocation will lead to more power loss and lower voltages, leading to higher operating costs in power grids. So, RDG units should be installed at optimal bus position with proper size. In this article, a novel Dolphin Echolocation Optimization (DEO) is presented to get optimal siting and sizing of RDG units simultaneously for diminishing power loss and ameliorating profile of voltage in the grid. The ability and robustness of the DEO is checked on IEEE-33 bus. The comparison with presented Genetic Algorithm (GA) and some recent literature works is done to affirm the efficacy and superiority of DEO technique. The simulation results have shown that DEO is the finest economical algorithm for finding the optimum positioning of RDG, leading to substantial loss mitigation and boost voltage profile compared to GA and other recent works.
配电网RDG机组优化配置新技术
在配电网中安装可再生分布式发电(RDG)机组是满足全球日益增长的能源需求的较好解决方案。RDG机组连接在用户侧,用于改善电压分布和减轻电网损耗。RDG机组在配置不当的情况下集成,会造成更大的功率损耗和更低的电压,从而导致电网运行成本的提高。因此,RDG机组应安装在最佳母线位置,尺寸合适。本文提出了一种新的海豚回声定位优化方法(DEO),以同时获得RDG机组的最佳位置和尺寸,以减小功率损耗和改善电网电压分布。在IEEE-33总线上验证了DEO的性能和鲁棒性。通过与现有遗传算法(GA)和一些最新文献的比较,肯定了DEO技术的有效性和优越性。仿真结果表明,与遗传算法和其他近期研究成果相比,DEO是寻找RDG最佳位置的最经济算法,可以显著降低损耗和升压分布。
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:481959085
Book学术官方微信