Spectral Variation-Based Signal Compression Technique for Gapless Power Quality Waveform Recording in Smart Grids

The current scenario of electric power systems expansion requires the insertion of new devices and technologies, contributing to the establishment of smart grids. However, the more instruments are connected to the grid, the greater the amount of data resulting from the measurements, which can cause a bottleneck in data transferring. The present article addresses this problem by proposing a system that implements a novel and efficient real-time data compression method based on the power signal spectral content variation, focused on long-term gapless oscillographic analysis. This system also provides a high-fidelity reconstruction for full oscillography power quality analysis. Comparison results with synthetic and real signals using another gapless power quality disturbance recorder present in literature and a commercial power quality disturbance recorder show that the proposed technique is capable to achieve a compression rate more than ten times greater than both while providing a better reconstruction quality, reaching compression ratio values of up to 10780:1 for synthetic signals and 9470:1 for real signals.

Automated summary

This article proposes a real-time data compression method based on the power signal spectral content variation to address the bottleneck issue in data transferring for expanding electric power systems. The method provides high-fidelity reconstruction for long-term gapless oscillographic analysis and achieves a compression rate more than ten times greater than other existing techniques, with compression ratio values of up to 10780:1 for synthetic signals and 9470:1 for real signals.