Power quality disturbance analysis based on wavelet transform and improved Prony method

Abstract

The traditional analysis method for power quality only analyzes one kind of specific problems. In order to effectively distinguish and identify common power disturbance signal, an algorithm combining wavelet analysis with Prony method is proposed. Firstly, the wavelet multi-resolution analysis is introduced, the appropriate wavelet function is proposed to decompose the disturbance signal and whether the decomposed signal modulus maxima exist is judged. Thus the steady state and transient state power quality disturbance problems are distinguished. For the transient disturbance problem, Mallat refactoring layer is optimized, the transient disturbance waveform are extracted and the type of disturbance is distinguished. For the steady disturbance problem, the process of estimating system order by Prony method and the accuracy of parameter identification are improved. Finally, mixed disturbance signals are analyzed and the simulation and experimental verification are performed by Matlab. Results of simulation and experiments show that the proposed method algorithm can accurately identify the various types of power quality disturbance signal.