Fault Diagnosis of Electric Transmission Lines Using Modular Neural Networks

This paper proposes a new method for fault diagnosis in electric power systems based on neural networks. With this method the diagnosis is performed by assigning a neural module for each type of component of the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up. The neural module for transmission lines also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents, as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network, nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.