{"title":"偏心随机密钥遗传算法在径向配电系统优化配置中的应用","authors":"Rommel Vargas, R. Romero, J. Franco","doi":"10.1109/TDC-LA.2018.8511718","DOIUrl":null,"url":null,"abstract":"The optimal reconfiguration of radial Electrical Distribution Systems (EDSs) is a classical optimization problem that deals with the operation of the system and is of great interest to the electricity sector. Although there is a large number of approaches in the specialized literature to solve this problem, the solution of the reconfiguration problem for large-scale EDSs is still difficult. This paper proposes a method to solve the reconfiguration problem of EDSs that is based on the specialized metaheuristic Biased Random-Key Genetic Algorithm, which showed excellent performance on the solution of complex problems in operational research. Tests carried out using a wellknown EDS demonstrate the efficiency of the proposed method.","PeriodicalId":267301,"journal":{"name":"2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA)","volume":"409 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems\",\"authors\":\"Rommel Vargas, R. Romero, J. Franco\",\"doi\":\"10.1109/TDC-LA.2018.8511718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The optimal reconfiguration of radial Electrical Distribution Systems (EDSs) is a classical optimization problem that deals with the operation of the system and is of great interest to the electricity sector. Although there is a large number of approaches in the specialized literature to solve this problem, the solution of the reconfiguration problem for large-scale EDSs is still difficult. This paper proposes a method to solve the reconfiguration problem of EDSs that is based on the specialized metaheuristic Biased Random-Key Genetic Algorithm, which showed excellent performance on the solution of complex problems in operational research. Tests carried out using a wellknown EDS demonstrate the efficiency of the proposed method.\",\"PeriodicalId\":267301,\"journal\":{\"name\":\"2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA)\",\"volume\":\"409 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TDC-LA.2018.8511718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D-LA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDC-LA.2018.8511718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
The optimal reconfiguration of radial Electrical Distribution Systems (EDSs) is a classical optimization problem that deals with the operation of the system and is of great interest to the electricity sector. Although there is a large number of approaches in the specialized literature to solve this problem, the solution of the reconfiguration problem for large-scale EDSs is still difficult. This paper proposes a method to solve the reconfiguration problem of EDSs that is based on the specialized metaheuristic Biased Random-Key Genetic Algorithm, which showed excellent performance on the solution of complex problems in operational research. Tests carried out using a wellknown EDS demonstrate the efficiency of the proposed method.