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

Eder Barboza Kapisch, Victor Valadares de Morais, Leandro Rodrigues Manso Silva, L. Manhaes de Andrade Filho, Carlos A. Duque

2021IEEE Transactions on Industrial Informatics19 citationsDOI

Abstract

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.

Topics & Concepts

Gapless playbackWaveformBottleneckComputer scienceSmart gridElectronic engineeringSIGNAL (programming language)Power (physics)Data compressionElectric power systemReal-time computingElectrical engineeringEngineeringVoltageEmbedded systemAlgorithmQuantum mechanicsOperating systemProgramming languagePhysicsPower Quality and HarmonicsBlind Source Separation TechniquesAdvanced Electrical Measurement Techniques
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