Feature extraction of power quality disturbances using adaptive harmonic wavelet transform

Feature extraction of a disturbed power signal provides information that helps to detect the responsible fault for power quality disturbance. A precise and faster feature extraction tool helps power engineers to monitor and maintain power disturbances more efficiently. This paper uses adaptive harmonic wavelet transform as a power quality feature extraction tool which can perform better to analyze a disturbed voltage or current signal compared to present methods. Adaptive harmonic wavelet transform adopts harmonic wavelet as a basis function which provides better representation of power quality signals than the other wavelet functions that are being employed in present analysis tools. Adaptive harmonic wavelet transform is derived from generalized harmonic wavelet transform by developing its adaptiveness to analyze all kinds of disturbed signals with minimum human interaction.