PMU data analysis in smart grid using WPD

Abstract

In this paper, a wavelet packet decomposition (WPD) based technique is proposed for the analysis, denoising and compression of the power system data in the smart grid (SG). WPD is an expansion of the wavelet decomposition (WD) tree algorithm to a full binary tree. The main advantage of the WPD is better signal representation by finding the best tree from a number of bases of the WPD. Thus, the wavelet packet analysis is an excellent pre-processing step for data analysis, denoising and compression, which provides satisfactory preservation of feature integrity and removal of redundancy to achieve better noise reduction and higher compression with controlled degradation in data fidelity. The proposed technique for SG will lead to a potential application for remote power protection and power quality monitoring. The data analysis, compression and denoising are performed through selection of a suitable wavelet function, decomposition the signal up to the optimum level, determination of the best tree representation, application of the threshold to the coefficients, and reconstruction of the signal. The proposed method is evaluated using a set of simulated and real phasor measurement unit (PMU) data. Comparative results are presented with the wavelet decomposition (WD).