Uncertainty Analysis of a Test Bed for Calibrating Voltage Transformers Vs. Temperature

Abstract

The paper addresses the evaluation of the uncertainty sources of a test bed system for calibrating voltage transformers vs. temperature. In particular, the Monte Carlo method has been applied in order to evaluate the effects of the uncertainty sources in two different conditions: by using the nominal accuracy specifications of the elements which compose the setup, or by exploiting the results of their metrological characterization. In addition, the influence of random effects on the system accuracy has been quantified and evaluated. From the results, it emerges that the choice of the uncertainty evaluation method affects the overall study. As a matter of fact, the use of a metrological characterization or of accuracy specifications provided by the manufacturers provides respectively an accuracy of 0.1 and 0.5 for the overall measurement setup.

Testing Rogowski Coils with Merging Units for Smart Grids

“…It is essential to highlight that the distribution of the phase error appears to be normal, which is in contrast to the assumption of a uniform distribution often made when employing the Monte Carlo method [29].…”

“…Linearity, temperature and temporal stability, standard calibration, and other factors that have a significant impact on LPCT error measurements mean that the probability distribution of the uncertainty that impacts the calculated ratio/phase error can be considered normal [29].…”

Testing Rogowski Coil with Digital Output for Smart Grid

“…The uncertainty resulting from the measurement chain (RC+MU) that is under calibration can be shown in Figure 3. Based on the assumption that the uncertainty that affects measurement errors should be less than one fifth of the limitations given by the accuracy class [24], and based on the results obtained, the suggested setting can be adopted, which can be used to calibrate RCs with accuracy class 0.5.…”

“…Linearity, temperature and temporal stability, standard calibration, and other factors that have a significant impact on LPCT errors measurements mean that the probability distribution of the uncertainty that impacts the calculated ratio/ phase error can be considered normal [24].…”

Low-Power Voltage Transformer Smart Frequency Modeling and Output Prediction up to 2.5 kHz, Using Sinc-Response Approach

“…[ 3 , 4 , 5 ] represent the efforts on the installation, traceability and challenges of integration in LPVTs. The uncertainty analysis of the ITs and their calibration test bed as a key factor for measurement, is performed in [ 6 , 7 , 8 , 9 , 10 ], while the nonlinearity compensation is assessed in [ 11 ] for voltage and current ITs. The application of ITs in the power network considering different network features is analyzed in research works such as [ 12 , 13 , 14 , 15 ].…”