{"title":"基于遗传算法的竞争电网总传输能力计算","authors":"M. Shaaban, Y. Ni, F. Wu","doi":"10.1109/DRPT.2000.855648","DOIUrl":null,"url":null,"abstract":"The application of the genetic algorithms to solve the total transfer capability (TTC) problem is proposed in this paper. TTC is a nonlinear function of the system operating conditions and security constraints. The objective of the proposed genetic algorithm is to maximize a specific point-to-point power transaction without system constraint violation and to determine the TTC between the two points through global optimal search. The suggested genetic algorithm is simple to implement and can easily incorporate various constraints. The floating-point based genetic algorithm was tested on a 4 bus test system with good convergence. The test results are compared favorably with that obtained from the continuation power flow.","PeriodicalId":127287,"journal":{"name":"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Total transfer capability calculations for competitive power networks using genetic algorithms\",\"authors\":\"M. Shaaban, Y. Ni, F. Wu\",\"doi\":\"10.1109/DRPT.2000.855648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of the genetic algorithms to solve the total transfer capability (TTC) problem is proposed in this paper. TTC is a nonlinear function of the system operating conditions and security constraints. The objective of the proposed genetic algorithm is to maximize a specific point-to-point power transaction without system constraint violation and to determine the TTC between the two points through global optimal search. The suggested genetic algorithm is simple to implement and can easily incorporate various constraints. The floating-point based genetic algorithm was tested on a 4 bus test system with good convergence. The test results are compared favorably with that obtained from the continuation power flow.\",\"PeriodicalId\":127287,\"journal\":{\"name\":\"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DRPT.2000.855648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DRPT.2000.855648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Total transfer capability calculations for competitive power networks using genetic algorithms
The application of the genetic algorithms to solve the total transfer capability (TTC) problem is proposed in this paper. TTC is a nonlinear function of the system operating conditions and security constraints. The objective of the proposed genetic algorithm is to maximize a specific point-to-point power transaction without system constraint violation and to determine the TTC between the two points through global optimal search. The suggested genetic algorithm is simple to implement and can easily incorporate various constraints. The floating-point based genetic algorithm was tested on a 4 bus test system with good convergence. The test results are compared favorably with that obtained from the continuation power flow.