Comparison of Fourier Transform and Wavelet Packet Transform for quantification of power quality

The measure of power quality is very vital in power systems for the proper operation. Power quality is quantified via Power Quality Indices (PQIs). High power quality (PQ) level represents one of the main objectives towards Power system. The currently used Power Quality Indices (PQIs) that are a measure of the PQ level are defined based on the Fourier Transform that produces unrealistic results in case of nonstationary PQ disturbances. The paper presents reformulated version of present PQIs based on Wavelet Packet Transform (WPT). The paper also explores the WPT capabilities in accurately analyzing non-stationary waveforms and providing a uniform frequency sub-bands leading to identifying more frequency components especially at high frequency. A few case studies are presented considering stationary and non-stationary to prove the accuracy of proposed WPT based PQIs. Upon testing with different types of wavelets, Daubechies 43 is found to be suitable, requiring less number of wavelet coefficients and hence reducing the data size. The paper presents crest factor, Total demand distortion, harmonic factor and THD adapted to inductance based on FT and WPT.