{"title":"超导发电机效率优化的遗传算法设计","authors":"Sangil Han, I. Muta, T. Hoshino, T. Nakamura","doi":"10.1109/ICEMS.2001.970631","DOIUrl":null,"url":null,"abstract":"This paper deals with a design method for the efficiency optimization of 223 MVA class superconducting generator. In consideration of the electrical characteristics based on electromagnetic analysis, GA (genetic algorithm), which has been successfully applied to various design problems in electric machines and devices, is used as an approach method of the optimized design with some variables and constraints. The results designed by this method are found to be reasonable and effective as compared with those obtained by the methods of trial and error until now.","PeriodicalId":143007,"journal":{"name":"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"GA design for efficiency optimization of a superconducting generator\",\"authors\":\"Sangil Han, I. Muta, T. Hoshino, T. Nakamura\",\"doi\":\"10.1109/ICEMS.2001.970631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with a design method for the efficiency optimization of 223 MVA class superconducting generator. In consideration of the electrical characteristics based on electromagnetic analysis, GA (genetic algorithm), which has been successfully applied to various design problems in electric machines and devices, is used as an approach method of the optimized design with some variables and constraints. The results designed by this method are found to be reasonable and effective as compared with those obtained by the methods of trial and error until now.\",\"PeriodicalId\":143007,\"journal\":{\"name\":\"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEMS.2001.970631\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMS.2001.970631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GA design for efficiency optimization of a superconducting generator
This paper deals with a design method for the efficiency optimization of 223 MVA class superconducting generator. In consideration of the electrical characteristics based on electromagnetic analysis, GA (genetic algorithm), which has been successfully applied to various design problems in electric machines and devices, is used as an approach method of the optimized design with some variables and constraints. The results designed by this method are found to be reasonable and effective as compared with those obtained by the methods of trial and error until now.
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