Neural network approach to fault classification for high speed protective relaying

This paper presents a new approach to fault classification for high speed protective relaying and show its effectiveness in computer simulations on parallel transmission lines. The scheme is based on the use of neural network architecture and implementation of digital signal processing concepts. We begin by classifying several fault types like 1-phase-to-ground, 2-phase-to-ground and 3-phase-to-ground faults. We proceed with classification of arcing and nonarcing faults in order to obtain a successful automatic reclosing. Encouraging results are shown and indicate that this approach can be used for supporting a new generation of very high speed protective relaying systems. >