{"title":"Distribution Network Reconfiguration Using Augmented Grey Wolf Optimization Algorithm for Power Loss Minimization","authors":"Hanan Hamour, S. Kamel, L. Nasrat, Juan Yu","doi":"10.1109/ITCE.2019.8646595","DOIUrl":null,"url":null,"abstract":"This paper proposes augmented Grey wolf optimizer (AGWO) for solving the radial distribution network reconfiguration problem. In the developed algorithm, the optimal switches combination is determined to change the topological structure of the system and reduce the total real power losses subject to the system operating constraints. AGWO inspired from behavior of the alpha α, and beta β grey wolves in the nature. The proposed algorithm is tested on IEEE 33-bus radial distribution system. The simulation results prove reasonable computing time and high performance of the proposed method comparing with other well-known optimization techniques.","PeriodicalId":391488,"journal":{"name":"2019 International Conference on Innovative Trends in Computer Engineering (ITCE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Innovative Trends in Computer Engineering (ITCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCE.2019.8646595","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
This paper proposes augmented Grey wolf optimizer (AGWO) for solving the radial distribution network reconfiguration problem. In the developed algorithm, the optimal switches combination is determined to change the topological structure of the system and reduce the total real power losses subject to the system operating constraints. AGWO inspired from behavior of the alpha α, and beta β grey wolves in the nature. The proposed algorithm is tested on IEEE 33-bus radial distribution system. The simulation results prove reasonable computing time and high performance of the proposed method comparing with other well-known optimization techniques.