Integration design of fuzzy system using genetic algorithm for improvement of voltage profile with Static VAR compensator

E. Saeidpour, M. Abedi, V.S. Parizy
{"title":"Integration design of fuzzy system using genetic algorithm for improvement of voltage profile with Static VAR compensator","authors":"E. Saeidpour, M. Abedi, V.S. Parizy","doi":"10.1109/OPTIM.2008.4602372","DOIUrl":null,"url":null,"abstract":"This paper proposed control of static VAR compensator (SVC) for improvement of voltage profile with fuzzy controller that tuned with genetic algorithm. Our method integrated two design stages; determinations of membership function and rules consequent parameters, because these stages may not be independent, it's important to consider them simultaneously to obtain optimal fuzzy systems. We present new method for insert genetic algorithm into fuzzy controller designation for non-linear and variable system. System equation is non-linear and not-clear and we can't use usual method for designation. We used from MATLAB simulator, for our simulations.","PeriodicalId":244464,"journal":{"name":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OPTIM.2008.4602372","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This paper proposed control of static VAR compensator (SVC) for improvement of voltage profile with fuzzy controller that tuned with genetic algorithm. Our method integrated two design stages; determinations of membership function and rules consequent parameters, because these stages may not be independent, it's important to consider them simultaneously to obtain optimal fuzzy systems. We present new method for insert genetic algorithm into fuzzy controller designation for non-linear and variable system. System equation is non-linear and not-clear and we can't use usual method for designation. We used from MATLAB simulator, for our simulations.
基于遗传算法的模糊系统改进与静态无功补偿的集成设计
本文提出了用遗传算法调谐的模糊控制器来控制静态无功补偿器(SVC)以改善电压分布。我们的方法集成了两个设计阶段;隶属函数和规则后续参数的确定,由于这些阶段可能不是独立的,因此同时考虑它们对于获得最优模糊系统是很重要的。提出了将遗传算法引入非线性变量系统模糊控制器设计的新方法。系统方程是非线性的、不清晰的,不能用通常的方法来表示。我们使用了MATLAB模拟器进行模拟。
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