{"title":"基于微遗传算法的分布式发电优化定位","authors":"C. Nayanatara, J. Baskaran, D. Kothari","doi":"10.1109/ICCPEIC.2014.6915419","DOIUrl":null,"url":null,"abstract":"The introduction of Distributed Generation (DG) devices for power system increases the stability, reduction in losses and increase in the cost of generation. In this paper Micro Genetic Algorithm (MGA) a non conventional optimization technique is used to optimize the various parameters. The various parameters taken into consideration are their type, location and size of the DG devices. The simulation on a distribution system with steady state basis was performed by modelling DG with different types. The results are compared and justified with another search method like Micro Genetic Algorithm (MGA). The results reveal the benefits of this method, which makes it challenging for solving simultaneous optimization problems of DG device in a power system network.","PeriodicalId":176197,"journal":{"name":"2014 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimal location of Distributed Generation using micro-genetic algorithm\",\"authors\":\"C. Nayanatara, J. Baskaran, D. Kothari\",\"doi\":\"10.1109/ICCPEIC.2014.6915419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The introduction of Distributed Generation (DG) devices for power system increases the stability, reduction in losses and increase in the cost of generation. In this paper Micro Genetic Algorithm (MGA) a non conventional optimization technique is used to optimize the various parameters. The various parameters taken into consideration are their type, location and size of the DG devices. The simulation on a distribution system with steady state basis was performed by modelling DG with different types. The results are compared and justified with another search method like Micro Genetic Algorithm (MGA). The results reveal the benefits of this method, which makes it challenging for solving simultaneous optimization problems of DG device in a power system network.\",\"PeriodicalId\":176197,\"journal\":{\"name\":\"2014 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPEIC.2014.6915419\",\"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 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPEIC.2014.6915419","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 micro-genetic algorithm
The introduction of Distributed Generation (DG) devices for power system increases the stability, reduction in losses and increase in the cost of generation. In this paper Micro Genetic Algorithm (MGA) a non conventional optimization technique is used to optimize the various parameters. The various parameters taken into consideration are their type, location and size of the DG devices. The simulation on a distribution system with steady state basis was performed by modelling DG with different types. The results are compared and justified with another search method like Micro Genetic Algorithm (MGA). The results reveal the benefits of this method, which makes it challenging for solving simultaneous optimization problems of DG device in a power system network.