Computational intelligence technique for solving power scheduling optimization problem

N. Abdullah, I. Musirin, Muhammad Murtadha Othman
{"title":"Computational intelligence technique for solving power scheduling optimization problem","authors":"N. Abdullah, I. Musirin, Muhammad Murtadha Othman","doi":"10.1109/PEOCO.2010.5559233","DOIUrl":null,"url":null,"abstract":"Computational Intelligence technique has become a prominent technique in solving engineering optimization problem. One of the problems which can be addressed in this issue is problems related to power system optimization. This paper presents computational intelligence technique for solving power scheduling optimization problem. Evolutionary Programming technique has been applied to minimise total transmission loss; considering the scheduling of active power and controlling the reactive power as the main control variables. In this study, the control process of reactive power and scheduling of active power at all generators will help control the power flow in the system. This has given impact to the current flow which influences the total transmission loss. Validation through a reliability test system revealed its superiority. Verification performed through comparative studies with other optimization technique revealed that the proposed computational intelligence technique produced promising results.","PeriodicalId":379868,"journal":{"name":"2010 4th International Power Engineering and Optimization Conference (PEOCO)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 4th International Power Engineering and Optimization Conference (PEOCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PEOCO.2010.5559233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

Computational Intelligence technique has become a prominent technique in solving engineering optimization problem. One of the problems which can be addressed in this issue is problems related to power system optimization. This paper presents computational intelligence technique for solving power scheduling optimization problem. Evolutionary Programming technique has been applied to minimise total transmission loss; considering the scheduling of active power and controlling the reactive power as the main control variables. In this study, the control process of reactive power and scheduling of active power at all generators will help control the power flow in the system. This has given impact to the current flow which influences the total transmission loss. Validation through a reliability test system revealed its superiority. Verification performed through comparative studies with other optimization technique revealed that the proposed computational intelligence technique produced promising results.
求解电力调度优化问题的计算智能技术
计算智能技术已成为解决工程优化问题的重要技术。其中一个可以解决的问题是与电力系统优化有关的问题。本文提出了求解电力调度优化问题的计算智能技术。进化规划技术已被应用于最小化总传输损耗;以有功功率调度和无功功率控制为主要控制变量。在本研究中,各发电机组的无功功率控制和有功功率调度过程将有助于控制系统的潮流。这对电流产生了影响,从而影响了总传输损耗。通过可靠性测试系统的验证显示了其优越性。通过与其他优化技术的比较研究进行验证,表明所提出的计算智能技术产生了有希望的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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