A network distribution power system fault location based on neural eigenvalue algorithm

A new approach to fault location for distribution network power system is presented. This approach uses the eigenvalue and an artificial neural network based learning algorithm. The neural network is trained to map the nonlinear relationship existing between fault location and characteristic eigenvalue The proposed approach is able to identify, to classify and to locate different types of faults such as: single-line-to-ground, double-line-to-ground, double-line and three-phase. Using the eigenvalue as neural network inputs the proposed algorithm is able to locate the fault distance. The results presented show the effectiveness of the proposed algorithm for correct fault diagnosis and fault location on a distribution power system networks.