Online Dynamic Assessment of System Stability using Unscented Kalman Filter

Abstract

Estimation systems based on PMU (Phasor Measurement Unit) data are a power system requirement based on the increasing expansion over the past decades. Kalman filter has been proved to be an adequate method for state estimation and data-driven methods. This paper applies the Unscented Kalman Filter to estimate in real-time the rotor angles. This paper proposes a predicting window as a time interval to forecast the rotor angle using real-time information. Emulated PMU sampling data have been used for carrying the simulations and have been validated using the 9-IEEE buses test system. The results confirm the method and the performance of the estimation.