{"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.