期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2007
卷号：7
期号：12
页码：282-286
出版社：International Journal of Computer Science and Network Security
摘要：This paper presents a new technique of accurate fault location system using artificial neural networks (ANN) for EHV teed feeder transmission lines. This technique utilizes voltage and current waveforms from one side of the three branches of the network to determine the accurate fault location. Variety of fault conditions are analyzed, trained and tested by the radial basis function neural network (RBFNN) using MATLAB. Fault detection, branch determination, fault classification and fault location are practiced. Results are obtained from training and testing of RBFNN and using ATP-EMTP for simulation of faulted data from a 500KV teed feeder transmission system.
