{"title":"Application of ANN to power system fault analysis","authors":"F.B. Lazim, N. Hamzah, P.M. Arsad","doi":"10.1109/SCORED.2002.1033109","DOIUrl":null,"url":null,"abstract":"This paper presents the computer architecture development using Artificial Neural Network (ANN) as an approach for predicting fault in a large interconnected transmission system. Transmission line faults can be classified using the bus voltage and line fault current. Monitoring the performance of these two factors are very useful for power system protection devices. The ANN is designed to be incorporated with a matrix based software tool MATLAB Version 6.0, which deals with fault diagnosis in power system. In MATLAB software modules, the balanced and unbalanced fault can be simulated. The data generated from this software are to be used as training and testing sets in the Neural Ware Simulator.","PeriodicalId":6865,"journal":{"name":"2016 IEEE Student Conference on Research and Development (SCOReD)","volume":"280 1","pages":"269-273"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Student Conference on Research and Development (SCOReD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCORED.2002.1033109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper presents the computer architecture development using Artificial Neural Network (ANN) as an approach for predicting fault in a large interconnected transmission system. Transmission line faults can be classified using the bus voltage and line fault current. Monitoring the performance of these two factors are very useful for power system protection devices. The ANN is designed to be incorporated with a matrix based software tool MATLAB Version 6.0, which deals with fault diagnosis in power system. In MATLAB software modules, the balanced and unbalanced fault can be simulated. The data generated from this software are to be used as training and testing sets in the Neural Ware Simulator.
本文介绍了利用人工神经网络(ANN)作为大型互联输电系统故障预测方法的计算机体系结构开发。传输线故障可以根据母线电压和线路故障电流进行分类。监测这两个因素的性能对电力系统保护装置非常有用。该神经网络设计与基于矩阵的MATLAB 6.0软件工具相结合,用于电力系统的故障诊断。在MATLAB软件模块中,可以对平衡故障和不平衡故障进行仿真。该软件生成的数据将用作Neural Ware Simulator的训练和测试集。