Evaluation of Power System Identification Methods and Their Applicability for Online PSS Tuning

This paper compares four methods and their accuracy in the identification of a simplified power system model. The identified model is to be used for power system stabilizer (PSS) tuning. Therefore, the focus is on identifying a low-order linear model that is able to accurately capture the dynamics of the system in the frequency bandwidth in which the PSS has typically to act in order to damp low frequency oscillations. We evaluate polynomial transfer function models and state space model structures under different estimation methods are considered. The two-area four-generator power system model is used as test case, and the results of the four methods are compared to the analytical results in terms of both low-frequency oscillation modes and frequency response in the 0.1 - 2Hz interval. The combination of the Predictor Based Subspace IDentification (PBSID) method and the Prediction-Error Minimization (PEM) method showed the better performance.