{"title":"基于专用遗传算法的配电网分布式发电分配","authors":"José Santos, L. P. G. Negrete, L. da Cunha Brito","doi":"10.1109/ISGTLatinAmerica52371.2021.9543022","DOIUrl":null,"url":null,"abstract":"This paper makes a comparison of distributed generation allocation in distribution networks using two algorithms based on Genetic Algorithms: the Compact Genetic Algorithm (CGA) and the Chu-Beasley Genetic Algorithm (CBGA). The operations conditions of the network are verified through the backward/forward sweep method. The objective function considered in the optimization model aims at minimizing of total active power losses in the system. The specialized algorithms are tested with three electrical systems: 10-bus, 34-bus, 70-bus and 126-bus and the obtained results show the convergence quickly and the robustness of the implemented algorithms.","PeriodicalId":120262,"journal":{"name":"2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Allocation of Distributed Generation in Distribution Networks Using Specialized Genetic Algorithms\",\"authors\":\"José Santos, L. P. G. Negrete, L. da Cunha Brito\",\"doi\":\"10.1109/ISGTLatinAmerica52371.2021.9543022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper makes a comparison of distributed generation allocation in distribution networks using two algorithms based on Genetic Algorithms: the Compact Genetic Algorithm (CGA) and the Chu-Beasley Genetic Algorithm (CBGA). The operations conditions of the network are verified through the backward/forward sweep method. The objective function considered in the optimization model aims at minimizing of total active power losses in the system. The specialized algorithms are tested with three electrical systems: 10-bus, 34-bus, 70-bus and 126-bus and the obtained results show the convergence quickly and the robustness of the implemented algorithms.\",\"PeriodicalId\":120262,\"journal\":{\"name\":\"2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISGTLatinAmerica52371.2021.9543022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTLatinAmerica52371.2021.9543022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Allocation of Distributed Generation in Distribution Networks Using Specialized Genetic Algorithms
This paper makes a comparison of distributed generation allocation in distribution networks using two algorithms based on Genetic Algorithms: the Compact Genetic Algorithm (CGA) and the Chu-Beasley Genetic Algorithm (CBGA). The operations conditions of the network are verified through the backward/forward sweep method. The objective function considered in the optimization model aims at minimizing of total active power losses in the system. The specialized algorithms are tested with three electrical systems: 10-bus, 34-bus, 70-bus and 126-bus and the obtained results show the convergence quickly and the robustness of the implemented algorithms.