{"title":"基于智能优化的分布式发电最优选址","authors":"A. Haidar","doi":"10.1109/ICTAI.2011.143","DOIUrl":null,"url":null,"abstract":"This paper proposes a method for optimal placement of DG based on intelligent optimization technique namely particle swarm optimization (PSO). Electrical system loss is used as an index of the proper location and sizing considering the DG bus voltage limit. The results show a significant reduction in power losses and considerable voltage improvement of the IEEE-30 bus test system.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Optimal Location of Distributed Generation Using Intelligent Optimization\",\"authors\":\"A. Haidar\",\"doi\":\"10.1109/ICTAI.2011.143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a method for optimal placement of DG based on intelligent optimization technique namely particle swarm optimization (PSO). Electrical system loss is used as an index of the proper location and sizing considering the DG bus voltage limit. The results show a significant reduction in power losses and considerable voltage improvement of the IEEE-30 bus test system.\",\"PeriodicalId\":332661,\"journal\":{\"name\":\"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTAI.2011.143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAI.2011.143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Location of Distributed Generation Using Intelligent Optimization
This paper proposes a method for optimal placement of DG based on intelligent optimization technique namely particle swarm optimization (PSO). Electrical system loss is used as an index of the proper location and sizing considering the DG bus voltage limit. The results show a significant reduction in power losses and considerable voltage improvement of the IEEE-30 bus test system.