Transmission Line Fault Detection and Classification: ANN Approach

Various tools are identified for transmission line fault identification and classification. The proposed algorithm is very helpful for advancement in relay such that the relay can be trained and will be able to detect and classify transmission line faults immediately. The transmission line faults have been simulated at different locations such as at 300, 600, and 900 km in MATLAB Simulink. The proposed method decomposes the signal into five detail-level using wavelets. The energy of five detail level components of various fault situations has been calculated. The premeditated energy is given as input to the artificial neural classifier. Classification accuracy up to 95.6% is obtained.