Online Calibration of Instrument Transformers Considering the Time-Varying Impedance of Transmission Lines

Instrument transformers (ITs) are fundamental but crucial measurement devices that provide accurate measurements for power systems. To maintain the stability of power systems, it is essential to conduct online calibration of ITs by replacing out-of-tolerance ITs with well-condition ones. Nevertheless, existing calibration methods do not consider the time-varying nature of transmission line (TL) impedance. Thus, the inaccurate assessment of the status of ITs may lead to improper replacement of ITs. To address this issue, we propose a novel method that incorporates the time-varying characteristics of TL parameters in online IT calibration. Generally, we formulate a bi-objective optimization problem based on Kirchhoff's voltage and current laws, where the measurement errors of ITs and TL parameters are the decision variables. Then, we propose a knowledge-assisted initialization strategy that incorporates the time-varying nature of TL parameters. Based on this, an improved trust-region reflective algorithm is proposed to optimize the optimization problem efficiently. The effectiveness and efficiency of the proposed method are examined via simulations. Compared with existing methods, the improved algorithm achieves a regression error of less than 0.01% while reducing the runtime by 93%.