Adaptive Subband Compression for Streaming of Continuous Point-on-Wave and PMU Data
Xinyi Wang, Yilu Liu, Lang Tong
TL;DR
The paper addresses real-time streaming of high-resolution CPOW and PMU data under strict accuracy requirements. It proposes Adaptive Subband Compression (ASBC), which partitions the spectrum into harmonic subbands at frequencies $kF_0$ plus an interharmonic band and uses a filterbank and activity detectors to adaptively transmit only active bands. A rate-distortion framework is developed with $R^{ASBC}=\sum_{k=1}^{K} p_k \frac{F_s}{S_k} R_k + p_e F_s R_e$ and $\eta^{ASBC}=\left(\sum_{k=1}^{K} p_k \frac{R_k}{R_Q S_k} + p_e \frac{R_e}{R_Q}\right)^{-1}$, and NMSE $\mathcal{E}^{ASBC}$ depends on subband activity detection accuracy. Empirical results on synthetic and real data (including UTK6K PMU/CPOW data) show ASBC achieves 100–1000:1 compression per subband while meeting industry NMSE standards, outperforming FFT-(k,L) and DWT baselines, and enabling continuous or burst-on-demand streaming in WAMS.
Abstract
A data compression system capable of providing real-time streaming of high-resolution continuous point-on-wave (CPOW) and phasor measurement unit (PMU) measurements is proposed. Referred to as adaptive subband compression (ASBC), the proposed technique partitions the signal space into subbands and adaptively compresses subband signals based on each subband's active bandwidth. The proposed technique conforms to existing industry phasor measurement standards, making it suitable for streaming high-resolution CPOW and PMU data either in continuous or burst on-demand/event-triggered modes. Experiments on synthetic and real data show that ASBC reduces the CPOW sampling rates by several orders of magnitude for real-time streaming while maintaining the precision required by industry standards.