2023
DOI: 10.21014/actaimeko.v12i3.1463
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Active power measurement uncertainty modelling and propagation analysis in case of harmonically distorted signals

Kiril Demerdziev,
Vladimir Dimchev

Abstract: The harmonic distortion of electrical waveforms results in a need for instruments’ performance evaluation in non-sinusoidal conditions. Specifications, which are valid for sine-wave input signals, are not supposed to be applied directly for uncertainty determination in case of harmonics, due to the non-linear dependence between the measured quantities and the single harmonic components’ magnitudes and phase shifts. Uncertainty calculation is especially challenging in case of power and/or energy measurements, b… Show more

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Cited by 2 publications
(2 citation statements)
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“…Both instruments record their readings simultaneously, and they are subsequently compared to one another [11,12]. Moreover, uncertainty estimation is very important factor in the field of metrology and measurement [13,14]. Researchers in [15] introduced a development of a testbed for the calibration/validation of static electricity meters under moderate-to-low power quality conditions.…”
Section: Introductionmentioning
confidence: 99%
“…Both instruments record their readings simultaneously, and they are subsequently compared to one another [11,12]. Moreover, uncertainty estimation is very important factor in the field of metrology and measurement [13,14]. Researchers in [15] introduced a development of a testbed for the calibration/validation of static electricity meters under moderate-to-low power quality conditions.…”
Section: Introductionmentioning
confidence: 99%
“…al. [4], deals with the challenge of uncertainty determination in the case of harmonics, due to the non-linear dependence between the measured quantities and the single harmonic components' magnitudes and phase shifts. A GUM-based perspective uniting single influence factors is applied and a simplified approach for the correlation coefficients calculation is adopted with experimental model validation.…”
mentioning
confidence: 99%