Metrological characterisation of current transformers calibration unit for accurate measurement

Isaiev, Valentyn; Velychko, Oleh

doi:10.21014/acta_imeko.v10i2.918

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…The MCM was applied in [ 34 , 35 ] for the evaluation of electrical quantities. Lastly, the application of the MCM allowed to evaluate the accuracy of two setups in [ 36 , 37 ].…”

Section: Uncertainty Evaluationmentioning

confidence: 99%

Simplified and Low-Cost Characterization of Medium-Voltage Low-Power Voltage Transformers in the Power Quality Frequency Range

Mingotti

Betti

Peretto

et al. 2022

Sensors

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The distribution network is experiencing a massive deployment of intelligent electronic devices (IEDs) such as energy meters, protective devices, and phasor measurement units (PMUs). This phenomenon resulted, on the one hand, in (i) the availability of distributed measurement systems capable of monitoring and collecting measurements from the distribution network, and (ii) increasing awareness of the system operator about the status of the network. On the other hand, such a significant number of devices require to be characterized, over the years, and assessed in both sinusoidal and distorted conditions. However, the characterization process may require a huge investment of money and time considering the low availability of reference instruments and accredited laboratories. To this purpose, this paper presents a simple and fast test procedure, performed with cheap and low-voltage instrumentation, to characterize two off-the-shelf low-power medium-voltage sensors in the power quality frequency range. In detail, the paper describes the measurement setup developed for the characterization and the performed tests. In addition, the method was also reproduced with reference equipment for validation purposes. Lastly, for both tests, an uncertainty evaluation was performed to quantify the goodness of the proposed method. From the results, it is possible to appreciate that the designed cheap and simple test can achieve as accurate results as those of a sophisticated and expensive equipment.

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“…The MCM was applied in [ 34 , 35 ] for the evaluation of electrical quantities. Lastly, the application of the MCM allowed to evaluate the accuracy of two setups in [ 36 , 37 ].…”

Section: Uncertainty Evaluationmentioning

confidence: 99%

Simplified and Low-Cost Characterization of Medium-Voltage Low-Power Voltage Transformers in the Power Quality Frequency Range

Mingotti

Betti

Peretto

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…To quantify and access the factors that affect the outcome of a measurement process through MCM, there are two methodologies that can provide this information: sensitivity analysis and a measurement uncertainty analysis [14], [15], [16], [17]. Both of them are now applied to AI models, the first one to analyze how much each uncertainty weights on the measurement of the model's outcome and the second to identify and quantify what are the main sources of uncertainties in the measurement [18].…”

Section: Introductionmentioning

confidence: 99%

Impact of the measurement uncertainty on the monitoring of thermal comfort through AI predictive algorithms

et al. 2021

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This paper presents an approach to assess the measurement uncertainty of human thermal comfort by using an innovative method that comprises a heterogeneous set of data, made by physiological and environmental quantities, and artificial intelligence algorithms, using Monte Carlo method (MCM). The dataset is made up of heart rate variability (HRV) features, air temperature, air velocity and relative humidity. Firstly, MCM is applied to compute the measurement uncertainty of the HRV features: results have shown that among 13 participants, there are uncertainty values in the measurement of HRV features that ranges from ±0.01% to ±0.7 %, suggesting that the uncertainty can be generalized among different subjects. Secondly, MCM is applied by perturbing the input parameters of random forest (RF) and convolutional neural network (CNN) algorithm, trained to measure human thermal comfort. Results show that environmental quantities produce different uncertainty on the thermal comfort: RF has the highest uncertainty due to the air temperature (14 %), while CNN has the highest uncertainty when relative humidity is perturbed (10.5 %). A sensitivity analysis also shows that air velocity is the parameter that causes a higher deviation of thermal comfort

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Methodological Aspects of Using Comparators for Metrological Traceability of Instrument Transformers

Isaiev¹,

Anokhin²

2022

Applied Aspects of Modern Metrology

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Instrument transformers are widely used in accounting the electricity as well as in protecting the energy generation systems. The accuracy of both voltage and current transformers is a critical parameter in terms of ensuring the reliability of functioning whether high-voltage or low-voltage networks. Two approaches are predominant in characterizing the voltage transformers with high primary rated voltage, these are applying either reference capacitor or reference transformer. Both methods require a device that enables the comparison of either two currents or two voltages. The errors of current transformers are determined by using the means of comparing two secondary currents, one of which is an output of reference transformer and the other is an output of a device under test. The calibration of such comparators may be a very sophisticated procedure. As metrological traceability depends on the measuring instruments and working standards used in calibration, the application of the proposed specific combinations of measuring instruments allows identifying the metrological traceability routes when calibrating the comparators.

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Metrological characterisation of current transformers calibration unit for accurate measurement

Cited by 3 publications

References 17 publications

Simplified and Low-Cost Characterization of Medium-Voltage Low-Power Voltage Transformers in the Power Quality Frequency Range

Simplified and Low-Cost Characterization of Medium-Voltage Low-Power Voltage Transformers in the Power Quality Frequency Range

Impact of the measurement uncertainty on the monitoring of thermal comfort through AI predictive algorithms

Methodological Aspects of Using Comparators for Metrological Traceability of Instrument Transformers

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