Detection of Faults in Power System Using Wavelet Transform and Independent Component Analysis

摘要

Uninterruptible power supply is the main motive of power utility companiesthat motivate them for identifying and locating the different types of faultsas quickly as possible to protect the power system prevent complete power blackouts using intelligent techniques. Thus, the present research work presents anovel method for detection of fault disturbances based on Wavelet Transform(WT) and Independent Component Analysis (ICA). The voltage signal is takenoffline under fault conditions and is being processed through wavelet and ICAfor detection. The time-frequency resolution from WT transform detects thefault initiation instant in the signal. Again, a performance index iscalculated from independent component analysis under fault condition which isused to detect the fault disturbance in the voltage signal. The proposedapproach is tested to be robust enough under various operating scenarios likewithout noise, with 20-dB noise and variation in frequency. Further, thedetection study is carried out using a performance index, energy content, byapplying the existing Fourier transform (FT), short time Fourier transform(STFT) and the proposed wavelet transform. Fault disturbances are detected ifthe energy calculated in each scenario is greater than the correspondingthreshold value. The fault detection study is simulated in MATLAB/Simulink fora typical power system.