PMU Based Problematic Parameter Identification Approach for Calibrating Generating Unit Models

Accurate model of generating unit plays a key role in power system modeling and simulation. To ensure the safe and stable operation of power grids, North American Electric Reliability Corporation requires that all generators larger than 10 MVA have to perform the model verification in every five years. However, the traditional key parameter identification based model calibration method cannot guarantee the accurate correction of the generator's problematic parameters, which have errors with their real values. The effectiveness of this kind model calibration method is still in doubt. To address the issues, this article developed a problematic-parameter-identification based generating unit model calibration approach. Trajectory sensitivity based sensitivity analysis is applied to determine the problematic parameter candidates (PPCs), which determine the dynamic responses of the system. Then, the Hilbert spectrum of PPCs and model output error curves are compared in time-frequency domain to screen out the problematic parameters. Also, the selected problematic parameters are calibrated with the measurements based identification technique. The effectiveness of the proposed method has been validated throughout a series testing cases from an actual hydropower plant integrated power system.