{"title":"Optimal re-configuration of micro-grids based on ranking of buses","authors":"M. Venkata Kirthiga, S. Gurunathan, S. A. Daniel","doi":"10.1109/ISET-INDIA.2011.6145370","DOIUrl":null,"url":null,"abstract":"Owing to urbanization and industrialization, there has been a steep increase in the electric power demand on contrary to the limited power generation facilities. This paper has attempted re-configuration of non-autonomous and autonomous micro-grids based on ranking of buses, formed with 60% and 100% penetration of the distributed generation respectively. Reconfiguration has been suggested in this work as a measure to improve the voltage profile of the system and to reduce the real power distribution losses. MATLAB code has been developed for ranking of buses based on loading capability and for optimal sizing of the DGs using Genetic algorithm and Particle Swarm Optimization techniques. The standard 33 bus distribution system has been used to validate the proposed reconfiguration algorithm.","PeriodicalId":265646,"journal":{"name":"ISGT2011-India","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISGT2011-India","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISET-INDIA.2011.6145370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Owing to urbanization and industrialization, there has been a steep increase in the electric power demand on contrary to the limited power generation facilities. This paper has attempted re-configuration of non-autonomous and autonomous micro-grids based on ranking of buses, formed with 60% and 100% penetration of the distributed generation respectively. Reconfiguration has been suggested in this work as a measure to improve the voltage profile of the system and to reduce the real power distribution losses. MATLAB code has been developed for ranking of buses based on loading capability and for optimal sizing of the DGs using Genetic algorithm and Particle Swarm Optimization techniques. The standard 33 bus distribution system has been used to validate the proposed reconfiguration algorithm.
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