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

The chapter delves into the critical challenge of system stability and control in complex power transmission networks, highlighting the necessity for continuous monitoring of dynamic states. It introduces the Unscented Kalman Filter (UKF) as a robust solution for dynamic state estimation in a multi-source isolated power system, addressing the limitations of traditional methods like the Extended Kalman Filter (EKF). The UKF is shown to effectively handle non-linearities and disturbances, providing accurate state estimates even under dynamic conditions and uncertainties. The chapter presents a detailed model of a single area power system integrated with renewable energy sources and electric vehicle reserves, and demonstrates the implementation and performance of the UKF through extensive simulation studies. The results highlight the UKF's ability to accurately estimate states under various disruptions and uncertainties, outperforming the EKF in terms of root mean square error. The chapter concludes by emphasizing the potential of the UKF for future applications in power system control and stability.