{"title":"配电网中分布式发电机的最优选址与规模","authors":"Samir Dahal, H. Salehfar","doi":"10.1109/NAPS.2013.6666866","DOIUrl":null,"url":null,"abstract":"Using a combination of Particle Swarm Optimization (PSO) and Newton-Raphson load flow methods this paper investigates the impact of location and size of distributed generators on distribution systems. Similar to the existing improved analytical (IA) method, the proposed approach optimizes the size and location of distributed generators with both real and reactive power capabilities. However, studies show that the proposed method yields much better results than the IA technique and with less computation times. In addition, compared to other evolutionary algorithms such as artificial bee colony (ABC), the proposed method achieves a better distribution system voltage profile with smaller DG sizes. To show the advantages of the proposed method, the IEEE 69-bus distribution system is used as a test bed and the results are compared with those from IA and ABC approaches.","PeriodicalId":421943,"journal":{"name":"2013 North American Power Symposium (NAPS)","volume":"48 21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Optimal location and sizing of distributed generators in distribution networks\",\"authors\":\"Samir Dahal, H. Salehfar\",\"doi\":\"10.1109/NAPS.2013.6666866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Using a combination of Particle Swarm Optimization (PSO) and Newton-Raphson load flow methods this paper investigates the impact of location and size of distributed generators on distribution systems. Similar to the existing improved analytical (IA) method, the proposed approach optimizes the size and location of distributed generators with both real and reactive power capabilities. However, studies show that the proposed method yields much better results than the IA technique and with less computation times. In addition, compared to other evolutionary algorithms such as artificial bee colony (ABC), the proposed method achieves a better distribution system voltage profile with smaller DG sizes. To show the advantages of the proposed method, the IEEE 69-bus distribution system is used as a test bed and the results are compared with those from IA and ABC approaches.\",\"PeriodicalId\":421943,\"journal\":{\"name\":\"2013 North American Power Symposium (NAPS)\",\"volume\":\"48 21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS.2013.6666866\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.2013.6666866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal location and sizing of distributed generators in distribution networks
Using a combination of Particle Swarm Optimization (PSO) and Newton-Raphson load flow methods this paper investigates the impact of location and size of distributed generators on distribution systems. Similar to the existing improved analytical (IA) method, the proposed approach optimizes the size and location of distributed generators with both real and reactive power capabilities. However, studies show that the proposed method yields much better results than the IA technique and with less computation times. In addition, compared to other evolutionary algorithms such as artificial bee colony (ABC), the proposed method achieves a better distribution system voltage profile with smaller DG sizes. To show the advantages of the proposed method, the IEEE 69-bus distribution system is used as a test bed and the results are compared with those from IA and ABC approaches.