{"title":"利用混合PSOGSA算法优化潮流","authors":"Jordan Radosavljević, N. Arsic, M. Jevtic","doi":"10.1109/RTUCON.2014.6998173","DOIUrl":null,"url":null,"abstract":"This paper presents a new hybrid algorithm based on the particle swarm optimization (PSO) and the gravitational search algorithm (GSA) for solving the optimal power flow (OPF) in power systems. Performance of this approach for the OPF problem is studied and evaluated on the standard IEEE 30-bus test system with different objective functions. Simulation results on the OPF problem show that the hybrid PSOGSA algorithm provides effective and robust high-quality solution.","PeriodicalId":259790,"journal":{"name":"2014 55th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Optimal power flow using hybrid PSOGSA algorithm\",\"authors\":\"Jordan Radosavljević, N. Arsic, M. Jevtic\",\"doi\":\"10.1109/RTUCON.2014.6998173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new hybrid algorithm based on the particle swarm optimization (PSO) and the gravitational search algorithm (GSA) for solving the optimal power flow (OPF) in power systems. Performance of this approach for the OPF problem is studied and evaluated on the standard IEEE 30-bus test system with different objective functions. Simulation results on the OPF problem show that the hybrid PSOGSA algorithm provides effective and robust high-quality solution.\",\"PeriodicalId\":259790,\"journal\":{\"name\":\"2014 55th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 55th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTUCON.2014.6998173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 55th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON.2014.6998173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a new hybrid algorithm based on the particle swarm optimization (PSO) and the gravitational search algorithm (GSA) for solving the optimal power flow (OPF) in power systems. Performance of this approach for the OPF problem is studied and evaluated on the standard IEEE 30-bus test system with different objective functions. Simulation results on the OPF problem show that the hybrid PSOGSA algorithm provides effective and robust high-quality solution.
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