基于蚁狮优化的配电网配电网发电规划

Z. M. Yasin, M. Rusdi, Z. Zakaria
{"title":"基于蚁狮优化的配电网配电网发电规划","authors":"Z. M. Yasin, M. Rusdi, Z. Zakaria","doi":"10.1109/PECon48942.2020.9314408","DOIUrl":null,"url":null,"abstract":"This paper proposed a method to determine the optimal location and sizing of Distributed Generation (DG) for power loss minimization using Ant Lion optimizer (ALO). The analysis also covers the effect of DG installation to voltage improvement and maximum system loadability index. ALO is an optimization algorithm that based on the nature interaction between ants and antlions. The nature interaction consists of five steps of hunting prey such as random walk of ants, building traps, entrapment of ants in traps, catching preys, and rebuilding traps. The ALO algorithm is tested on IEEE 69-bus distribution test system. The system will find the optimal location and sizing with corresponding load increase until it reaches the maximum system loadability (MSL) of the network. DG are usually attached to the end terminal at the load side of the system that refers to a technology that generate electricity at or near where it will be used such as solar panels and combined heat and power. The result of test function shows that the proposed algorithm can provide accurate yet competitive result in terms of power loss minimization, maximum system loadability enhancement and consistency.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"69 1","pages":"182-187"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Distribution Generation Planning in Distribution Network using Ant Lion Optimizer\",\"authors\":\"Z. M. Yasin, M. Rusdi, Z. Zakaria\",\"doi\":\"10.1109/PECon48942.2020.9314408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposed a method to determine the optimal location and sizing of Distributed Generation (DG) for power loss minimization using Ant Lion optimizer (ALO). The analysis also covers the effect of DG installation to voltage improvement and maximum system loadability index. ALO is an optimization algorithm that based on the nature interaction between ants and antlions. The nature interaction consists of five steps of hunting prey such as random walk of ants, building traps, entrapment of ants in traps, catching preys, and rebuilding traps. The ALO algorithm is tested on IEEE 69-bus distribution test system. The system will find the optimal location and sizing with corresponding load increase until it reaches the maximum system loadability (MSL) of the network. DG are usually attached to the end terminal at the load side of the system that refers to a technology that generate electricity at or near where it will be used such as solar panels and combined heat and power. The result of test function shows that the proposed algorithm can provide accurate yet competitive result in terms of power loss minimization, maximum system loadability enhancement and consistency.\",\"PeriodicalId\":6768,\"journal\":{\"name\":\"2020 IEEE International Conference on Power and Energy (PECon)\",\"volume\":\"69 1\",\"pages\":\"182-187\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Power and Energy (PECon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PECon48942.2020.9314408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Power and Energy (PECon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PECon48942.2020.9314408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

提出了一种利用蚂蚁狮子优化器(ALO)确定分布式发电(DG)的最优位置和最优规模的方法。分析了DG安装对电压改善和系统最大负荷指标的影响。蚁群优化算法是一种基于蚁群与蚁群之间自然相互作用的优化算法。自然互动包括蚂蚁的随机行走、设置陷阱、将蚂蚁困在陷阱中、捕捉猎物和重建陷阱五个步骤。在IEEE 69总线配电测试系统上对ALO算法进行了测试。随着负载的增加,系统将找到最优的位置和规模,直到达到网络的最大系统负载能力(MSL)。DG通常附着在系统负载侧的终端上,这是指在使用地点或附近发电的技术,如太阳能电池板和热电联产。测试函数的结果表明,该算法在最小化功耗、最大限度地提高系统负载性和一致性方面能够提供准确而有竞争力的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distribution Generation Planning in Distribution Network using Ant Lion Optimizer
This paper proposed a method to determine the optimal location and sizing of Distributed Generation (DG) for power loss minimization using Ant Lion optimizer (ALO). The analysis also covers the effect of DG installation to voltage improvement and maximum system loadability index. ALO is an optimization algorithm that based on the nature interaction between ants and antlions. The nature interaction consists of five steps of hunting prey such as random walk of ants, building traps, entrapment of ants in traps, catching preys, and rebuilding traps. The ALO algorithm is tested on IEEE 69-bus distribution test system. The system will find the optimal location and sizing with corresponding load increase until it reaches the maximum system loadability (MSL) of the network. DG are usually attached to the end terminal at the load side of the system that refers to a technology that generate electricity at or near where it will be used such as solar panels and combined heat and power. The result of test function shows that the proposed algorithm can provide accurate yet competitive result in terms of power loss minimization, maximum system loadability enhancement and consistency.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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