DOI:10.1007/s40565-018-0424-2 |
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Wavelet-based data compression for wide-area measurement data of oscillations |
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Net amount: 1737 |
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Author:
Lin CHENG1, Xinchi JI1, Fang ZHANG1, He HUANG2, Song GAO2
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Author Affiliation:
1. State Key Laboratory of Control and Simulation of Power System and Generation Equipment, Tsinghua University, Beijing, China
2. State Grid Jiangsu Electric Power Company, Nanjing, China
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Foundation: |
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Abstract: |
This paper proposes a wavelet-based data compression
method to compress the recorded data of oscillations
in power systems for wide-area measurement
systems. Actual recorded oscillations and simulated oscillations
are compressed and reconstructed by the waveletbased
data compression method to select the best wavelet
functions and decomposition scales according to the criterion
of the minimum compression distortion composite
index, for a balanced consideration of compression performance
and reconstruction accuracy. Based on the
selections, the relationship between the oscillation frequency
and the corresponding optimal wavelet and scale is
discussed, and a piecewise linear model of the base-2
logarithm of the frequency and the order of the wavelet is
developed, in which different pieces represent different
scales. As a result, the wavelet function and decomposition
scale can be selected according to the oscillation frequency.
Compared with the wavelet-based data compression
method with a fixed wavelet scale for disturbance
signals and the real-time data compression method based
on exception compression and swing door trending for
oscillations, the proposed method can provide high compression
ratios and low distortion rates. |
Keywords: |
Data compression, Oscillation, Wavelettransform, Wide-area measurement system (WAMS) |
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Online Time:2018/11/11 |
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