Estimation of synchronous generator parameters using an adaptive parameter estimator

System identification in state space form, particularly when physical parameters of a system are required, has certain advantages. In this paper, nonlinear parameter estimation of synchronous generators using an adaptive parameter estimator is addressed. Although it is assumed that the model is linearized w.r.t. states, it still remains nonlinear and time-varying w.r.t. the parameters. The parameter estimation algorithm is based on gradient method in least squares and simultaneously uses Kalman filter to cope with the process noise. The proposed method is first applied to a third order nonlinear model of a synchronous generator and then it is used to identify the equivalent parameters of the external system as well. The parameters used in the simulation are those previously identified for a particular power system. In this study, the field voltage is considered as the input and the active output power and the terminal voltage are considered as the outputs of the synchronous generator.