Fault detection and classification technique in EHV transmission lines based on Artificial Neural Networks

This paper investigates a new approach based on Artificial Neural Networks (ANNs) for real-time fault detection and classification in power transmission lines which can be used in digital power system protection. The Fault Detector and Classifier (FDC) consists of four independent ANNs. The technique uses consecutive magnitude current and voltage data at one terminal as inputs to the corresponding ANN. The ANN outputs are used to indicate simultaneously the presence and the type of the fault. The FDC is tested under different fault types, fault locations, fault resistances and fault inception angles. All test results show that the proposed FDC can be used for very high speed digital relaying. Copyright (c) 2005 John Wiley & Sons, Ltd.