{"title":"在实际配电系统中利用无功优化降低功率损耗","authors":"Hamza Yapici, N. Çetinkaya","doi":"10.1109/INISTA.2015.7276731","DOIUrl":null,"url":null,"abstract":"Electrical power losses are an important factor for the operation of power systems. Reactive power optimization can reduce power loss. This paper describes the solution of reactive power optimization problem using particle swarm optimization and genetic algorithm. The numerical analysis has been carried out in a part of real power system in Turkey that is managed by MEDAŗ. The goal of this study is minimizing the active power loss of the whole distribution network. Due to the absence of any generators in the distribution network, shunt capacitors and bus voltages are taken as control variables. The values of control variables are determined by the both algorithms and the results are compared.","PeriodicalId":136707,"journal":{"name":"2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Reduction of power loss using reactive power optimization in a real distribution system\",\"authors\":\"Hamza Yapici, N. Çetinkaya\",\"doi\":\"10.1109/INISTA.2015.7276731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electrical power losses are an important factor for the operation of power systems. Reactive power optimization can reduce power loss. This paper describes the solution of reactive power optimization problem using particle swarm optimization and genetic algorithm. The numerical analysis has been carried out in a part of real power system in Turkey that is managed by MEDAŗ. The goal of this study is minimizing the active power loss of the whole distribution network. Due to the absence of any generators in the distribution network, shunt capacitors and bus voltages are taken as control variables. The values of control variables are determined by the both algorithms and the results are compared.\",\"PeriodicalId\":136707,\"journal\":{\"name\":\"2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INISTA.2015.7276731\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INISTA.2015.7276731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reduction of power loss using reactive power optimization in a real distribution system
Electrical power losses are an important factor for the operation of power systems. Reactive power optimization can reduce power loss. This paper describes the solution of reactive power optimization problem using particle swarm optimization and genetic algorithm. The numerical analysis has been carried out in a part of real power system in Turkey that is managed by MEDAŗ. The goal of this study is minimizing the active power loss of the whole distribution network. Due to the absence of any generators in the distribution network, shunt capacitors and bus voltages are taken as control variables. The values of control variables are determined by the both algorithms and the results are compared.