Excitation System Parameters Estimation by Different Input Signals and Various Kalman Filters

The excitation system is one of the most crucial components of a power plant. Knowing the exact parameters of the excitation system and their changes over time is essential for efficient and accurate power system dynamic studies. In this paper, the parameters of a typical and well-known type of excitation system are estimated using different types of Kalman filters, including unscented Kalman filter (UKF), spherical-simplex Kalman filter (SS-UKF), and cubature Kalman filter (CKF). The efficacy of these Kalman filter methods in the excitation system parameters estimation problem is investigated under three different planned and unplanned events as the input of the methods. The planned disturbances will be internal type (a reference voltage step) and external type (unit transformer tap changing) whereas the unplanned disturbance is caused by power grid events (neighbor generator outage). Comparison is done between the simulation results and experimental ones and the best appropriate approach is selected.

Keywords:

Excitation system , parameters identification , Kalman Filter