HIGH-SPEED FAULT-DETECTION AND CLASSIFICATION WITH NEURAL NETS

This paper introduces a new neural net (NN) approach for automated fau lt disturbance detection and classification. The NN design and impleme ntation are aimed at high-speed processing which can provide selective real-time detection and classification of faults. The approach is ext ensively tested using the Electromagnetic Transients Program (EMTP) si mulations of two quite complex transmission system configurations. The results indicate that the speed and selectivity of the approach are q uite adequate for a number of different transmission and distribution monitoring, control, and protection applications.