{"title":"Optimal power flow solution by a modified particle swarm optimization algorithm","authors":"H. Hajian-Hoseinabadi, S. H. Hosseini, M. Hajian","doi":"10.1109/UPEC.2008.4651443","DOIUrl":null,"url":null,"abstract":"This paper presents a modified particle swarm optimization (MPSO) algorithm for solving the optimal power flow (OPF) problems. The main distinction of this approach is in using particlepsilas worth experience in stead of the best previous experience. The proposed approach is evaluated on the IEEE 30-bus test system which minimizes the total fuel cost considering operational constraints such as power flow equations, transmission flow limits, bus voltages and reactive power of generators. The results obtained using the proposed approach are compared with results of other optimization methods.","PeriodicalId":287461,"journal":{"name":"2008 43rd International Universities Power Engineering Conference","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 43rd International Universities Power Engineering Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPEC.2008.4651443","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
This paper presents a modified particle swarm optimization (MPSO) algorithm for solving the optimal power flow (OPF) problems. The main distinction of this approach is in using particlepsilas worth experience in stead of the best previous experience. The proposed approach is evaluated on the IEEE 30-bus test system which minimizes the total fuel cost considering operational constraints such as power flow equations, transmission flow limits, bus voltages and reactive power of generators. The results obtained using the proposed approach are compared with results of other optimization methods.