{"title":"Development of artificial neural network for voltage stability monitoring","authors":"S. Sahari, A. F. Abidin, T. Rahman","doi":"10.1109/PECON.2003.1437413","DOIUrl":null,"url":null,"abstract":"This paper presents the development and an application artificial neural network (ANN) based method for predicting of voltage stability index in power system network. The main feature of this paper is to introduce the approach in developing neural network backpropagation by using C programming and its accuracy in predicting voltage stability index in the power system network. The training developed neural network was accomplished by using real power Pd and reactive power Qd at each load bus as input information, and voltage stability index L information covering stability at each individual load bus as output information. The generalization capability of the developed neural networks under large number of random operation of loading conditions has been tested. Fast performance, accurate evaluation and good prediction for voltage stability index have been obtained. Results of tests conducted on IEEE 6-bus test system are presented and discussed.","PeriodicalId":136640,"journal":{"name":"Proceedings. National Power Engineering Conference, 2003. PECon 2003.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. National Power Engineering Conference, 2003. PECon 2003.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PECON.2003.1437413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
This paper presents the development and an application artificial neural network (ANN) based method for predicting of voltage stability index in power system network. The main feature of this paper is to introduce the approach in developing neural network backpropagation by using C programming and its accuracy in predicting voltage stability index in the power system network. The training developed neural network was accomplished by using real power Pd and reactive power Qd at each load bus as input information, and voltage stability index L information covering stability at each individual load bus as output information. The generalization capability of the developed neural networks under large number of random operation of loading conditions has been tested. Fast performance, accurate evaluation and good prediction for voltage stability index have been obtained. Results of tests conducted on IEEE 6-bus test system are presented and discussed.