Embedded-Zerotree-Wavelet-Based Data Denoising and Compression for Smart Grid

In this paper, an embedded zerotree wavelet transform (EZWT)-based technique is employed for the data denoising and compression in the smart grid (SG). The EZWT is a simple but effective data compression algorithm. This technique does not need any training, prestored tables or codebooks, and prior knowledge of the data source. In this paper, the analysis and subsequent compression and denoising properties of the EZWT are examined for power system signals in SG. The proposed approach is evaluated using phasor measurement units and power system data. Experimental results demonstrate that the presented method both compresses the signal and depresses the noise contained in the signal. Comparative compression and noise removal results are presented with the wavelet transform.