PMU data analysis in smart grid using WPD

In this paper, a wavelet packet decomposition (WPD) based technique is proposed for denoising and compression of the power system data in the smart grid (SG). WPD, which is an expansion of the wavelet decomposition (WD) tree algorithm to a full binary tree, offers better signal representation than WD by finding the best tree from a number of bases of the WPD. Thus, for data denoising and compression, WPD 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 data compression and denoising tasks 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).