Dynamic State Estimation of a Multi-source Isolated Power System Using Unscented Kalman Filter

In power systems, dynamic state estimation (DSE) is a crucial activity for real-time monitoring and control to ensure the system's safe and efficient operation. This paper presents an method for real-time estimation of dynamic states of an isolated power system integrated with renewable energy sources (RESs) and electric vehicles (EVs) aggregates. The proposed method employs an adapted unscented Kalman filter (UKF) as an observer to estimate the system's dynamic states which are either inaccessible or corrupted with measurement noise. MATLAB/Simulink is used to develop a simulation platform for frequency response model of power system. The simulation results on the developed test system investigated the efficacy of UKF as dynamic state estimator that takes into account the diverse behaviours of the system and provides accurate estimates of the system states.