Dynamic stability enhancement with fuzzy based power system stabilizer tuned by hottest non-traditional optimization technique

M. Linda, N. Kesavan Nair
{"title":"Dynamic stability enhancement with fuzzy based power system stabilizer tuned by hottest non-traditional optimization technique","authors":"M. Linda, N. Kesavan Nair","doi":"10.1109/ICCCNT.2010.5591736","DOIUrl":null,"url":null,"abstract":"The supplementary control signal is provided by means of Power System Stabilizer (PSS), will damp the low frequency oscillations. This paper presents the design of fuzzy logic based power system stabilizers using genetic algorithms in multimachine power system. In the proposed fuzzy expert system, generator speed deviation and its derivative are chosen as input signals to fuzzy logic based power system stabilizer. In this approach centers of membership functions and the parameters of the fuzzy logic controllers has been tuned using genetic algorithm. Inclusion of GA in tuning fuzzy logic based power system stabilizer will provide good damping and significantly reduces computational time in the design process. Simulation results on multimachine system subjected to small perturbation and three phase fault show the effectiveness and robustness of the proposed PSS over a wide range of operating conditions and system configurations. The problem of optimizing the membership functions and the parameters of fuzzy logic based power system stabilizer is converted into an optimization problem and which is solved by genetic algorithm with the integral of squared time squared error (ISTSE) based objective function.","PeriodicalId":134352,"journal":{"name":"2010 Second International conference on Computing, Communication and Networking Technologies","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International conference on Computing, Communication and Networking Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2010.5591736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

Abstract

The supplementary control signal is provided by means of Power System Stabilizer (PSS), will damp the low frequency oscillations. This paper presents the design of fuzzy logic based power system stabilizers using genetic algorithms in multimachine power system. In the proposed fuzzy expert system, generator speed deviation and its derivative are chosen as input signals to fuzzy logic based power system stabilizer. In this approach centers of membership functions and the parameters of the fuzzy logic controllers has been tuned using genetic algorithm. Inclusion of GA in tuning fuzzy logic based power system stabilizer will provide good damping and significantly reduces computational time in the design process. Simulation results on multimachine system subjected to small perturbation and three phase fault show the effectiveness and robustness of the proposed PSS over a wide range of operating conditions and system configurations. The problem of optimizing the membership functions and the parameters of fuzzy logic based power system stabilizer is converted into an optimization problem and which is solved by genetic algorithm with the integral of squared time squared error (ISTSE) based objective function.
基于最热门非传统优化技术的模糊电力系统稳定器动态稳定性增强
通过电力系统稳定器(PSS)提供补充控制信号,抑制低频振荡。本文提出了基于模糊逻辑的多机电力系统稳定器的遗传算法设计。在该模糊专家系统中,选择发电机转速偏差及其导数作为基于模糊逻辑的电力系统稳定器的输入信号。该方法采用遗传算法对模糊控制器的隶属函数中心和参数进行了整定。将遗传算法应用于基于模糊逻辑的电力系统稳定器的整定中,不但具有良好的阻尼效果,而且大大减少了设计过程中的计算时间。在小扰动和三相故障下的多机系统仿真结果表明,所提出的PSS在广泛的运行条件和系统配置下具有有效性和鲁棒性。将基于模糊逻辑的电力系统稳定器的隶属函数和参数优化问题转化为优化问题,并采用基于时间误差平方积分(ISTSE)的遗传算法求解。
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