A square root filter algorithm for dynamic state estimation of electric power systems

The proper analysis and successful operation of a power system implies a reliable estimate of its state. As a result state estimation (SE) is nowadays considered as the heart of modern control centers. Several dynamic state estimation algorithms based on the extended Kalman filtering theory (EKF) have been proposed in the literature but, as has been reported, numerical problems may arise in its implementation in practice. To circumvent the problems inherent to the Kalman filter algorithm the authors present in this paper an algorithm for power system state estimation based on the square root filtering technique. The estimator proposed is decoupled in nature due to modifications made in the measurement equations resulting in a new observation model