K. Tao, Cheng Haozhong, Hu Zechun, Wang Chun, Huang Wei, Chen Chunqin, Gao Yubo
{"title":"基于ComGIS网络分析和MOGA的开环配电网多目标规划","authors":"K. Tao, Cheng Haozhong, Hu Zechun, Wang Chun, Huang Wei, Chen Chunqin, Gao Yubo","doi":"10.1109/DRPT.2008.4523614","DOIUrl":null,"url":null,"abstract":"In this paper, an advanced method for the planning of open-loop medium voltage (MV) distribution network is proposed. The multiobjective planning model is constructed, and a special multiobjective genetic algorithm (MOGA) is designed based on the network dataset built by component geographical information systems (ComGIS). The network analysis function of the ComGIS is embedded in the overall optimization process to find single-loop optimal paths. Crossover and mutation operator are designed according to characteristics of the coding. The evolutionary orientation is directed by the fitness function based on Pareto order of individuals. The Pareto optimal set (POS) including several candidate planning schemes is gotten through MOGA, from which the recommended scheme is selected. The method has been applied to real life power distribution networks, showing its potential in practical applications.","PeriodicalId":240420,"journal":{"name":"2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Multiobjective planning of open-loop mv distribution networks using ComGIS network analysis and MOGA\",\"authors\":\"K. Tao, Cheng Haozhong, Hu Zechun, Wang Chun, Huang Wei, Chen Chunqin, Gao Yubo\",\"doi\":\"10.1109/DRPT.2008.4523614\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an advanced method for the planning of open-loop medium voltage (MV) distribution network is proposed. The multiobjective planning model is constructed, and a special multiobjective genetic algorithm (MOGA) is designed based on the network dataset built by component geographical information systems (ComGIS). The network analysis function of the ComGIS is embedded in the overall optimization process to find single-loop optimal paths. Crossover and mutation operator are designed according to characteristics of the coding. The evolutionary orientation is directed by the fitness function based on Pareto order of individuals. The Pareto optimal set (POS) including several candidate planning schemes is gotten through MOGA, from which the recommended scheme is selected. The method has been applied to real life power distribution networks, showing its potential in practical applications.\",\"PeriodicalId\":240420,\"journal\":{\"name\":\"2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DRPT.2008.4523614\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DRPT.2008.4523614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiobjective planning of open-loop mv distribution networks using ComGIS network analysis and MOGA
In this paper, an advanced method for the planning of open-loop medium voltage (MV) distribution network is proposed. The multiobjective planning model is constructed, and a special multiobjective genetic algorithm (MOGA) is designed based on the network dataset built by component geographical information systems (ComGIS). The network analysis function of the ComGIS is embedded in the overall optimization process to find single-loop optimal paths. Crossover and mutation operator are designed according to characteristics of the coding. The evolutionary orientation is directed by the fitness function based on Pareto order of individuals. The Pareto optimal set (POS) including several candidate planning schemes is gotten through MOGA, from which the recommended scheme is selected. The method has been applied to real life power distribution networks, showing its potential in practical applications.