Application of Kalman filter to improve model integrity for securing electricity delivery

Abstract

Power system model integrity is essential to many planning and operation tasks to ensure the safety and reliability of electricity delivery. Inaccurate system models would result in unreliable assessment of system security conditions and cause large-scale blackouts such as the 2003 Northeast Blackout. This dictates a strong need for model calibration and verification, which should be done periodically and preferably in an automatic manner. Our previous work has demonstrated the feasibility of applying Extended Kalman Filter (EKF) to calibrate generator parameters using disturbance data recorded by phasor measurement units (PMU). This paper proposes to use a Riccati equation to investigate EKF's performance, especially regarding parameter identifiability. The covariance, which can be derived from the Riccati equation, offers insight into the uncertainties of parameters estimated by the EKF-based method. Simulation results show the effectiveness of the proposed approach.