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

Area of Science:

• Metrology and Measurement Science
• Electrical Engineering
• Instrumentation and Control

Background:

• Accurate calibration of voltage transformers is crucial for power system reliability.
• Uncertainty evaluation in test bed systems is complex, influenced by various factors.
• Existing methods for uncertainty assessment may not fully capture system performance.

Purpose of the Study:

• To evaluate uncertainty sources in a test bed system for voltage transformer calibration against temperature.
• To compare the impact of using nominal accuracy specifications versus metrological characterization on uncertainty.
• To quantify the influence of random effects on the overall system accuracy.

Main Methods:

• Application of the Monte Carlo method for uncertainty evaluation.
• Analysis of uncertainty under two conditions: using nominal accuracy specifications and metrological characterization.
• Quantification and evaluation of random effects on system accuracy.

Main Results:

• The choice of uncertainty evaluation method significantly impacts the overall study results.
• Metrological characterization of components yielded an overall measurement setup accuracy of 0.1.
• Using nominal accuracy specifications resulted in an overall measurement setup accuracy of 0.5.

Conclusions:

• Metrological characterization provides a more accurate assessment of uncertainty compared to manufacturer specifications.
• The Monte Carlo method is effective for evaluating complex uncertainty sources in calibration test beds.
• Optimizing uncertainty evaluation methods is key to enhancing the precision of voltage transformer calibrations.