Title :
Repetitive learning control for the correction of wound-type potential transformer measurement errors: sensitivity analysis
Author :
Hamrita, Takoi K
Author_Institution :
Biol. & Agric. Eng., Georgia Univ., Athens, GA, USA
fDate :
4/1/2000 12:00:00 AM
Abstract :
Successful implementation of a transmission level harmonic measurement system requires accurate and reliable measurement of harmonic voltages and currents. Existing substation instrument transformers are designed for harmonic-free 60 Hz measurements. Hence, their use to measure harmonics leads to the introduction of resonance as well as saturation errors in the measurements. An online error correction method to correct for wound-type potential transformer measurement errors has been proposed in previous publications. The error correction was formulated as an output tracking problem where the distorted measurements were used along with the experimentally developed transformer model to reconstruct the transformer input. The scope of this paper is to develop a sensitivity analysis for the error correction method with respect to the transformer parameters. Results of this analysis indicate that the sensitivity of the method with respect to the transformer parameters is quite low
Keywords :
electric current measurement; error correction; instrument transformers; measurement errors; potential transformers; power system harmonics; sensitivity analysis; transformer windings; voltage measurement; 60 Hz; error correction method; harmonic currents measurement; harmonic voltages measurement; output tracking problem; repetitive learning control; sensitivity analysis; substation instrument transformers; transformer parameters; transmission level harmonic measurement system; wound-type potential transformer measurement errors; Circuit faults; Current measurement; Distortion measurement; Error correction; Instrument transformers; Measurement errors; Resonance; Sensitivity analysis; Substations; Voltage transformers;
Journal_Title :
Power Delivery, IEEE Transactions on