arrow
Return

A Wavelet-Based Data Compression Technique for Smart Grid

delete2011-03-01
delete134
PRE
AI
J
Jianhui Wang
W
Wenzhong Gao
C
Cong Liu
DOI:10.1109/TSG.2010.2091291delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This paper proposes a wavelet-based data compression approach for the smart grid (SG). In particular, wavelet transform (WT)-based multiresolution analysis (MRA), as well as its properties, are studied for its data compression and denoising capabilities for power system signals in SG. Selection of the Order 2 Daubechies wavelet and scale 5 as the best wavelet function and the optimal decomposition scale, respectively, for disturbance signals is demonstrated according to the criterion of the maximum wavelet energy of wavelet coefficients (WCs). To justify the proposed method, phasor data are simulated under disturbance circumstances in the IEEE New England 39-bus system. The results indicate that WT-based MRA can not only compress disturbance signals but also depress the sinusoidal and white noise contained in the signals.
Keywords:
Data compression
disturbance analysis
wavelet transform
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Smart Grid cover
IEEE Transactions on Smart Grid
IF:
9.8
Papers:
5.7K
Citations:
4.3W

Organization

A
Argonne National Laboratory
Scholars:
1.1W
Papers: 9.2K
Citations: 3.8W
U
united states department of energy (doe)
Scholars:
11.3W
Papers: 9.6W
Citations: 246
E
enernex
Scholars:
17
Papers: 18
Citations: 0
researcher View more organizations