Detection and classification of faults in transmission lines based on wavelets

Optimal operation of a power system depends on how a fault location is accurately and quickly located, so that restoration and maintenance of power is accomplished. Fault detection, fault classification, needs to be performed using a fast responsive algorithm at different levels of a power system. Effect of factors such as fault impedance, fault inception angle (FIA), and fault distance, which cause disturbances in power line can be countered by Wavelet multi resolution analysis (MRA). The method of fault discrimination proposed in this work is on the basis of the three-phase current and voltage waveforms measured during the occurrence of fault in the power transmission-line. Further, a superior technique, viz. Wavelet Singular Entropy (WSE) is applied both at transmission line and transformer level which minimizes the noise in the fault transients and is unaffected by the transient magnitude. The proposed algorithm is verified using MATLAB/Simulink software and the obtained results prove that both MRA and WSE based fault detection and classification methods are practically feasible and reliable.