{"title":"基于遗传算法和广义约简梯度的分布式发电对配电网影响优化研究","authors":"S. R. Fahim, W. Helmy","doi":"10.1109/ICENGTECHNOL.2012.6396131","DOIUrl":null,"url":null,"abstract":"This paper presents the effect of Distributed Generators (DG) existence in the electrical power distribution networks taking IEEE 14 and IEEE 30 bus test feeders as proposed systems. The analysis is done to examine the effect on the overall system losses and voltage profile. The aim behind this study is to obtain the optimum location and penetration level of the added DG unit in order to decrease the losses and enhance the voltage profile. The optimization is done using two different optimization techniques, generalized reduced gradient (GRG) and genetic algorithm (GA). The power system dynamic program MATLAB is used for this study. The simulation results are analyzed to show the effectiveness of GA over the GRG algorithm.","PeriodicalId":149484,"journal":{"name":"2012 International Conference on Engineering and Technology (ICET)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Optimal study of distributed generation impact on electrical distribution networks using GA and generalized reduced gradient\",\"authors\":\"S. R. Fahim, W. Helmy\",\"doi\":\"10.1109/ICENGTECHNOL.2012.6396131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the effect of Distributed Generators (DG) existence in the electrical power distribution networks taking IEEE 14 and IEEE 30 bus test feeders as proposed systems. The analysis is done to examine the effect on the overall system losses and voltage profile. The aim behind this study is to obtain the optimum location and penetration level of the added DG unit in order to decrease the losses and enhance the voltage profile. The optimization is done using two different optimization techniques, generalized reduced gradient (GRG) and genetic algorithm (GA). The power system dynamic program MATLAB is used for this study. The simulation results are analyzed to show the effectiveness of GA over the GRG algorithm.\",\"PeriodicalId\":149484,\"journal\":{\"name\":\"2012 International Conference on Engineering and Technology (ICET)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Engineering and Technology (ICET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICENGTECHNOL.2012.6396131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Engineering and Technology (ICET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICENGTECHNOL.2012.6396131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal study of distributed generation impact on electrical distribution networks using GA and generalized reduced gradient
This paper presents the effect of Distributed Generators (DG) existence in the electrical power distribution networks taking IEEE 14 and IEEE 30 bus test feeders as proposed systems. The analysis is done to examine the effect on the overall system losses and voltage profile. The aim behind this study is to obtain the optimum location and penetration level of the added DG unit in order to decrease the losses and enhance the voltage profile. The optimization is done using two different optimization techniques, generalized reduced gradient (GRG) and genetic algorithm (GA). The power system dynamic program MATLAB is used for this study. The simulation results are analyzed to show the effectiveness of GA over the GRG algorithm.