Wavelet-based data compression for wide-area measurement data of oscillations

Wavelet-based data compression for wide-area measurement data of oscillations

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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 wavelet-based data compression method to select the best wavelet functions and decomposition jeff rosenstock buffalo 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 click here exception compression and swing door trending for oscillations, the proposed method can provide high compression ratios and low distortion rates.