A New Adaptive Hybrid Neural Network And Fuzzy Logic Based Fault Classification Approach For Transmission Lines Protection

Abstract: Dynamic neural networks have been applied in system identification and control for those systems for last few years. A wide class of nonlinear physical systems contains slow and fast dynamic processes that occur at different moments. An adaptive hybrid neural networks and fuzzy logic based algorithm is proposed in this research to classify fault types in transmission lines. The proposed method is able to identify all the available shunt faults in transmission lines with high level of robustness against variable conditions such as measured amplitudes and fault resistance. In this method, a two-end unsynchronized measurement of the signals is used which can be incorporated in digital distance relays that are able to be programmed, it can also be shared and discourse data with all protective and monitoring device. The process has been carried over by a number of simulations using in MATLAB software.

Keywords: Fuzzy Logic System, Adaptive Artificial Neural Networks, Transmission Lines Protection.