{"title":"基于粒子群优化的智能电网无功调度技术研究","authors":"I. Pisica, G. Taylor, Sebastian Traistaru","doi":"10.1109/UPEC.2014.6934596","DOIUrl":null,"url":null,"abstract":"This paper gives an overview of the Particle Swarm Optimization technique with the aim of investigating its applicability to minimizing losses in a power distribution system. The suitability of this method is investigated by emphasizing the impact of its intrinsic parameters on the results. The investigation employs particle swarm optimization on a test system by controlling the generator voltages, transformer taps and the reactive power in the capacitor banks for each load bus. In total it contains 33 control variables: 5 generators (not including the terminal bus), 4 transformers and 24 capacitor banks. A theoretical approach of the PSO is given in the beginning, followed by the simulation results and analyses.","PeriodicalId":414838,"journal":{"name":"2014 49th International Universities Power Engineering Conference (UPEC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Investigation of Particle Swarm Optimization as technique for reactive power dispatch in smart grids\",\"authors\":\"I. Pisica, G. Taylor, Sebastian Traistaru\",\"doi\":\"10.1109/UPEC.2014.6934596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper gives an overview of the Particle Swarm Optimization technique with the aim of investigating its applicability to minimizing losses in a power distribution system. The suitability of this method is investigated by emphasizing the impact of its intrinsic parameters on the results. The investigation employs particle swarm optimization on a test system by controlling the generator voltages, transformer taps and the reactive power in the capacitor banks for each load bus. In total it contains 33 control variables: 5 generators (not including the terminal bus), 4 transformers and 24 capacitor banks. A theoretical approach of the PSO is given in the beginning, followed by the simulation results and analyses.\",\"PeriodicalId\":414838,\"journal\":{\"name\":\"2014 49th International Universities Power Engineering Conference (UPEC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 49th International Universities Power Engineering Conference (UPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UPEC.2014.6934596\",\"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 49th International Universities Power Engineering Conference (UPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPEC.2014.6934596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Investigation of Particle Swarm Optimization as technique for reactive power dispatch in smart grids
This paper gives an overview of the Particle Swarm Optimization technique with the aim of investigating its applicability to minimizing losses in a power distribution system. The suitability of this method is investigated by emphasizing the impact of its intrinsic parameters on the results. The investigation employs particle swarm optimization on a test system by controlling the generator voltages, transformer taps and the reactive power in the capacitor banks for each load bus. In total it contains 33 control variables: 5 generators (not including the terminal bus), 4 transformers and 24 capacitor banks. A theoretical approach of the PSO is given in the beginning, followed by the simulation results and analyses.