Fault Diagnosis in Electric Power Transmission Systems

This book presents an effective approach to detection, classification and isolation (location) of faults in transmission line systems. The objective is to implement a complete scheme for distance protection of a transmission line system. In order to reach this goal, the distance protection task is subdivided into different neural networks for fault detection, fault identification (classification) as well as fault location in different zones. The other purpose of this work is to study and compare the application of three different neural network architectures for the protection of the transmission lines. The considered three approaches are back-propagation, radial basis functions and support vector machines. Simulation results are provided to demonstrate the advantages and disadvantages of these structures when applied to the problem of transmission line protection.