{"title":"Implementation of GCPSO for Multi-objective VAr Planning with SVC and Its Comparison with GA and PSO","authors":"M. Farsangi, H. Nezamabadi-pour, K.Y. Lee","doi":"10.1109/ISAP.2007.4441632","DOIUrl":null,"url":null,"abstract":"In this paper, Guaranteed Convergence Particle Swarm Optimization (GCPSO) Algorithm is used for VAr planning with the Static Var Compensators (SVC) in a large-scale power system. To enhance voltage stability, the planning problem is formulated as a multiobjective optimization problem for maximizing fuzzy performance indices. The multi-objective VAr planning problem is solved by the fuzzy GCPSO and the results are compared with those obtained by the Particle Swarm Optimization (PSO) and Genetic Algorithm","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Intelligent Systems Applications to Power Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAP.2007.4441632","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
In this paper, Guaranteed Convergence Particle Swarm Optimization (GCPSO) Algorithm is used for VAr planning with the Static Var Compensators (SVC) in a large-scale power system. To enhance voltage stability, the planning problem is formulated as a multiobjective optimization problem for maximizing fuzzy performance indices. The multi-objective VAr planning problem is solved by the fuzzy GCPSO and the results are compared with those obtained by the Particle Swarm Optimization (PSO) and Genetic Algorithm
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