Smart Grid Data Denoising and Compression Using Wavelet Packet Transform

Abstract

The efficient operation of the Smart Grid is contingent on the accurate analysis of power signals, which are often compromised by disturbances. These power signals, captured by quality monitors, generate substantial volumes of data, thereby necessitating effective compression strategies to facilitate manageable data transfer and collection. Besides mitigating the costs associated with data storage, transmission, and encryption, these compression techniques must ensure minimal reconstruction error to avoid distortion in the original signal. Moreover, it becomes imperative to eliminate noise for the attainment of high-quality signals, critical for disturbance detection. In this paper, a novel method has been developed employing lower-order wavelets (Db3, Db2, Db2, Db2, and Db1). This method decomposes the signal from the first to fifth level utilizing wavelet Packet Transform, testing the efficacy on Phasor Measurement Unit data. Simulation results demonstrate enhanced data compression and noise reduction compared to previous designs, with the signal being approximately reconstructed. This innovative approach offers a facile, efficient, economical, and time-saving solution for smart grid data management, marking a significant advancement in this field.