A Fast Iterative Method for Dynamic State Estimation with Unknown Noise Statistics

The extensive application of phasor measurement units (PMUs) provides a solid information foundation for real-time monitoring of power system dynamic processes. To improve the robustness of unscented Kalman filter (UKF), a spherical simplex unscented transform-based iterated unscented Kalman filter (SSUT-IUKF) is proposed. By introducing spherical simplex unscented transform and iterative correction technology into UKF, the computing efficiency and estimation accuracy have been effectively improved. Finally, simulation experiments are conducted on an IEEE 39-bus system. Compared with traditional dynamic state estimation methods for synchronous generators, SSUT- IUKF has potential advantages in algorithm robustness, computational efficiency and estimation accuracy.