DETECTION AND CLASSIFICATION OF TRANSMISSION LINES FAULTS USING DISCRETE WAVELET TRANSFORM AND ANN AS CLASSIFIER

Transmission line protection is an important issue in power system because 85-87% of power system faults are occurring in transmission line. This dissertation work gives technique to classify the different faults on transmission line for quick and reliable operation of protection schemes. It also a new technique for fast and accurate detection as well as classification of power system faults using modern signal processing techniques The technique involves wavelet analysis of faulty voltage and current waveforms, which are recorded at a suitable monitoring location in multi-bus power system to gather valuable information required in detection and classification of faults. Transmission line faults are of mainly five types: L-G, L-L, L-L-G, L-L-L and L-L-L-G. But the effect of L-L-L and L-L-L-G faults is same. So, here we are considering only L-L-L fault. In all four different faults are classified after faulty condition is detected in the system. With the advent of computers, it becomes easier to simulate a power system in various software’s available for simulation. Today, various simulation software’s like PSCAD, ATP and MATLAB/SIMULINK are available in the market. In this project, I have considered ‘Standard IEEE System’ and simulated it in PSCAD/EMTP software. The data obtained from simulation is exported to the Wavelet Toolbox of MATLAB for acquiring the various parameters like presence of harmonics and overvoltage