Application of extended Kalman filter techniques for dynamic model parameter calibration

Abstract

Phasor measurement has previously been used for sub-system model validation, which enables rigorous comparison of model simulation and recorded dynamics and facilitates identification of problematic model components. Recent work extends the sub-system model validation approach with a focus on how model parameters may be calibrated to match recorded dynamics. In this paper, a calibration method using Extended Kalman Filter (EKF) technique is proposed. This paper presents the formulation as well as case studies to show the validity of the EKF-based parameter calibration method. The proposed calibration method is expected to be a cost-effective means complementary to traditional equipment testing for improving dynamic model quality.