IEEE Transactions on Power Systems · 2022 · 14 citations · 21 references
EngineeringElectrical EngineeringMetrologyPower ElectronicsTime Series AnalysisDigital Signal ProcessingElectrical MeasurementElectrical MetrologyPower Grid AnalysisPower QualityTransmission LinesCurrent Measurement Data ProcessingLeast Squares EstimationLeast Squares ProblemsLow-rank ApproximationPower MeasurementSingular Value AnalysisSingular Value Decomposition
Recently a pragmatic data centric method to calibrate substation capacitive voltage transformers (CVT) by exploiting local redundancy in substation CVT PMU data has been proposed. It does not require any external reference CVT. This paper extends the above philosophy to current transformer (CT) calibration problem. Once a line terminals CVTs are calibrated, then estimate of the three phase line currents can be deduced. Currents in a bus, for each of the three phases sum to zero. Hence, the corresponding measurement matrix will be rank deficient. Singular value decomposition's low rank approximation property is used to filter the noise and then a linear least squares problem is solved to calibrate remaining substation CTs. The method then can be intrinsically extended to calibrate other CTs of the network without using other series line impedances. Results are presented with both simulated and field PMU data of 400 kV lines.
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Characterizing and quantifying noise in PMU data
Michael S. Brown, Milan Biswal, Sukumar Brahma et al. · 2016 · 252 citations
Mo-Shing Chen, W.E. Dillon · Proceedings of the IEEE · 1974 · 186 citations
Engineering, Electrical Engineering, Systems Engineering +17