High-speed fault detection and classification with neural nets

Abstract

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