An ANN Routine for Fault Detection, Classification, and Location in Transmission Lines

This article presents an Artificial Neural Network (ANN) approach to simulate a complete scheme for distance protection of transmission lines. The protection technique is based on a modular approach whereby different neural network modules have been adopted for fault detection, fault classification and fault location. Three-phase voltage and current samples were utilized as inputs for the proposed scheme. The Alternative Transients Program (ATP) software was used to generate data for the transmission line (400 kV). The results obtained show that the global performance of the ANN architectures is highly satisfactory under a wide variety of different fault conditions.