基于遗传算法的竞争电网总传输能力计算

M. Shaaban, Y. Ni, F. Wu
{"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}
引用次数: 15

摘要

本文将遗传算法应用于求解总传输能力问题。TTC是系统运行条件和安全约束的非线性函数。提出的遗传算法的目标是在不违反系统约束的情况下最大化特定的点对点电力交易,并通过全局最优搜索确定两点之间的TTC。所建议的遗传算法易于实现,并且可以很容易地合并各种约束。基于浮点数的遗传算法在4总线测试系统上进行了测试,具有良好的收敛性。试验结果与连续潮流的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信