Detection and Location of Transient Power Quality Disturbances Based on Morphology-complex Wavelet

A variety of impulses and white noises exist in the actual detection of transient power quality disturbances.These noises are obstructive to the accurate extraction of the transient disturbance signals of power quality.So,the effective filter ought to be designed to restrain these noises before the detection and location of transient power quality disturbances.In the way,the characteristics of the original signal can be well retained and the noise interferences are suppressed.Based on Mathematical Morphology theory,the generalized morphological filter is used as the preposed unit of the complex wavelet transform,which are combined as a novel approach of the morphology-complex wavelet detection algorithm.Simulations show that it can effectively filter white noise and impulse noise with the Signal-to-Noise-Ratio(SNR) increased and the Mean Square Error(MSE) decreased.In the paper,the complex wavelet derived by Daubechies real wavelet and its compound information are applied to detect and locate for the filtered results of power quality disturbances with noises.The voltage sag,high frequency oscillation,short-time harmonic and slight amplitude sag signals with noises are used to verify the validity of the filter-location approach respectively.Numerical simulation results show that the proposed detection approach based on morphology-complex wavelet transform is valid and effective.