{"title":"基于人工神经网络的电力系统稳态安全分析","authors":"M. Shukla, M. Abdelrahman","doi":"10.1109/SSST.2004.1295661","DOIUrl":null,"url":null,"abstract":"The focus of this paper is to present an artificial neural network based methodology to assess the steady state security of a power system. The security of the system is assessed on the basis of the voltage profile at each bus with reference to changes in generation and load in the system. The input to the neural network is the voltage level at each bus. The ANN used is a feedforward multilayer network trained with a backpropagation algorithm. The output of the ANN classifies the security of the power system into normal, alert and emergency states. An IEEE 14-bus system is considered to demonstrate the results of the methodology.","PeriodicalId":309617,"journal":{"name":"Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Artificial neural networks based steady state security analysis of power systems\",\"authors\":\"M. Shukla, M. Abdelrahman\",\"doi\":\"10.1109/SSST.2004.1295661\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The focus of this paper is to present an artificial neural network based methodology to assess the steady state security of a power system. The security of the system is assessed on the basis of the voltage profile at each bus with reference to changes in generation and load in the system. The input to the neural network is the voltage level at each bus. The ANN used is a feedforward multilayer network trained with a backpropagation algorithm. The output of the ANN classifies the security of the power system into normal, alert and emergency states. An IEEE 14-bus system is considered to demonstrate the results of the methodology.\",\"PeriodicalId\":309617,\"journal\":{\"name\":\"Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSST.2004.1295661\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.2004.1295661","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial neural networks based steady state security analysis of power systems
The focus of this paper is to present an artificial neural network based methodology to assess the steady state security of a power system. The security of the system is assessed on the basis of the voltage profile at each bus with reference to changes in generation and load in the system. The input to the neural network is the voltage level at each bus. The ANN used is a feedforward multilayer network trained with a backpropagation algorithm. The output of the ANN classifies the security of the power system into normal, alert and emergency states. An IEEE 14-bus system is considered to demonstrate the results of the methodology.