基于粒子群算法和探路者算法的最优无功调度

Q3 Computer Science International Journal of Computing Pub Date : 2022-12-31 DOI:10.47839/ijc.21.4.2775
S. A. Adegoke, Yanxia Sun
{"title":"基于粒子群算法和探路者算法的最优无功调度","authors":"S. A. Adegoke, Yanxia Sun","doi":"10.47839/ijc.21.4.2775","DOIUrl":null,"url":null,"abstract":"Optimum reactive power dispatch (ORPD) significantly impacts the operation and control of electrical power systems (EPS) due to its undeniable benefit in the economic operation and reliability of the systems. ORPD is a sub-problem of optimal power flow (OPF). The main aim is to reduce/minimize the real power loss. Among the swarm intelligence (SI) metaheuristic algorithms is particle swarm optimization (PSO), which has fast convergence speed and gives the optimum solution to a particular problem by moving the swarm in the intensification (exploitation) search space. Also, the pathfinder algorithm (PFA) mimics the collective movement of the swarms with a leading member. Therefore, combining the fast convergence of PSO with PFA to form a hybrid technique is considered a viable approach in this study to avoid decreasing PFA searchability when the dimension of the problem increases. In this article, a hybrid algorithm based on a particle swarm optimization and pathfinder algorithm (HPSO-PFA) is proposed for the first time to study the combination of the control variables (generator voltage, transformer tap, and sizing of reactive compensation to obtain the objective function (total real power loss). The proposed method is tested on the IEEE 30 and 118 bus systems. The losses were reduced to 16.14262 MW and 107.2913 MW for the IEEE 30 and 118 test systems. Furthermore, the percentage (%) reduction for the IEEE 30 and 118 test systems are 9.8% and 19.25%, respectively. The result demonstrates the performance of HPSO-PFA gives a better solution than the other algorithms.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimum Reactive Power Dispatch Solution using Hybrid Particle Swarm Optimization and Pathfinder Algorithm\",\"authors\":\"S. A. Adegoke, Yanxia Sun\",\"doi\":\"10.47839/ijc.21.4.2775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimum reactive power dispatch (ORPD) significantly impacts the operation and control of electrical power systems (EPS) due to its undeniable benefit in the economic operation and reliability of the systems. ORPD is a sub-problem of optimal power flow (OPF). The main aim is to reduce/minimize the real power loss. Among the swarm intelligence (SI) metaheuristic algorithms is particle swarm optimization (PSO), which has fast convergence speed and gives the optimum solution to a particular problem by moving the swarm in the intensification (exploitation) search space. Also, the pathfinder algorithm (PFA) mimics the collective movement of the swarms with a leading member. Therefore, combining the fast convergence of PSO with PFA to form a hybrid technique is considered a viable approach in this study to avoid decreasing PFA searchability when the dimension of the problem increases. In this article, a hybrid algorithm based on a particle swarm optimization and pathfinder algorithm (HPSO-PFA) is proposed for the first time to study the combination of the control variables (generator voltage, transformer tap, and sizing of reactive compensation to obtain the objective function (total real power loss). The proposed method is tested on the IEEE 30 and 118 bus systems. The losses were reduced to 16.14262 MW and 107.2913 MW for the IEEE 30 and 118 test systems. Furthermore, the percentage (%) reduction for the IEEE 30 and 118 test systems are 9.8% and 19.25%, respectively. The result demonstrates the performance of HPSO-PFA gives a better solution than the other algorithms.\",\"PeriodicalId\":37669,\"journal\":{\"name\":\"International Journal of Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47839/ijc.21.4.2775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47839/ijc.21.4.2775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 1

摘要

最优无功调度(ORPD)对电力系统的经济运行和可靠性有着不可否认的好处,对电力系统的运行和控制有着重要的影响。ORPD是最优潮流问题(OPF)的子问题。主要目的是减少/最小化实际功率损失。在群体智能(SI)的元启发式算法中,粒子群优化算法(PSO)收敛速度快,通过在强化(开发)搜索空间中移动群体来给出特定问题的最优解。此外,寻路者算法(PFA)模拟了具有领导成员的群体的集体运动。因此,结合粒子群算法和粒子群算法的快速收敛性,形成一种混合算法,避免了粒子群算法在问题维数增加时可搜索性下降的问题,是本研究的可行方法。本文首次提出了一种基于粒子群优化和寻路算法的混合算法(HPSO-PFA),研究了控制变量(发电机电压、变压器分接和无功补偿大小)的组合,以获得目标函数(总实际损耗)。该方法在ieee30和ieee118总线系统上进行了测试。ieee30和ieee118测试系统的损耗分别减少到16.14262 MW和107.2913 MW。此外,ieee30和ieee118测试系统的降低百分比分别为9.8%和19.25%。结果表明,HPSO-PFA算法的性能优于其他算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Optimum Reactive Power Dispatch Solution using Hybrid Particle Swarm Optimization and Pathfinder Algorithm
Optimum reactive power dispatch (ORPD) significantly impacts the operation and control of electrical power systems (EPS) due to its undeniable benefit in the economic operation and reliability of the systems. ORPD is a sub-problem of optimal power flow (OPF). The main aim is to reduce/minimize the real power loss. Among the swarm intelligence (SI) metaheuristic algorithms is particle swarm optimization (PSO), which has fast convergence speed and gives the optimum solution to a particular problem by moving the swarm in the intensification (exploitation) search space. Also, the pathfinder algorithm (PFA) mimics the collective movement of the swarms with a leading member. Therefore, combining the fast convergence of PSO with PFA to form a hybrid technique is considered a viable approach in this study to avoid decreasing PFA searchability when the dimension of the problem increases. In this article, a hybrid algorithm based on a particle swarm optimization and pathfinder algorithm (HPSO-PFA) is proposed for the first time to study the combination of the control variables (generator voltage, transformer tap, and sizing of reactive compensation to obtain the objective function (total real power loss). The proposed method is tested on the IEEE 30 and 118 bus systems. The losses were reduced to 16.14262 MW and 107.2913 MW for the IEEE 30 and 118 test systems. Furthermore, the percentage (%) reduction for the IEEE 30 and 118 test systems are 9.8% and 19.25%, respectively. The result demonstrates the performance of HPSO-PFA gives a better solution than the other algorithms.
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
International Journal of Computing
International Journal of Computing Computer Science-Computer Science (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
39
期刊介绍: The International Journal of Computing Journal was established in 2002 on the base of Branch Research Laboratory for Automated Systems and Networks, since 2005 it’s renamed as Research Institute of Intelligent Computer Systems. A goal of the Journal is to publish papers with the novel results in Computing Science and Computer Engineering and Information Technologies and Software Engineering and Information Systems within the Journal topics. The official language of the Journal is English; also papers abstracts in both Ukrainian and Russian languages are published there. The issues of the Journal are published quarterly. The Editorial Board consists of about 30 recognized worldwide scientists.
期刊最新文献
Website Quality Measurement of Educational Government Agency in Indonesia using Modified WebQual 4.0 A Comparative Study of Data Annotations and Fluent Validation in .NET Attr4Vis: Revisiting Importance of Attribute Classification in Vision-Language Models for Video Recognition The Improved Method for Identifying Parameters of Interval Nonlinear Models of Static Systems Image Transmission in WMSN Based on Residue Number System
×
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