{"title":"Power system equivalent based on an artificial neural network","authors":"I. Pavić, Z. Hebel, M. Delimar","doi":"10.1109/ITI.2001.938042","DOIUrl":null,"url":null,"abstract":"Very often, insufficient data is exchanged between neighboring power systems for quality load flow and contingency analysis. The external systems, therefore, have to be substituted with the power system equivalents. In this paper the possibilities of using an artificial neural network as the external power system equivalent is explored, to be used for load flow and contingency analysis within the internal power system. The experiment is performed on a standard IEEE 24-node network which is, for the purposes of testing, divided into two systems (the internal and the external) and the external system is modeled by a neural network. The results are presented and discussed.","PeriodicalId":375405,"journal":{"name":"Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITI.2001.938042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Very often, insufficient data is exchanged between neighboring power systems for quality load flow and contingency analysis. The external systems, therefore, have to be substituted with the power system equivalents. In this paper the possibilities of using an artificial neural network as the external power system equivalent is explored, to be used for load flow and contingency analysis within the internal power system. The experiment is performed on a standard IEEE 24-node network which is, for the purposes of testing, divided into two systems (the internal and the external) and the external system is modeled by a neural network. The results are presented and discussed.