A Study on State Estimation of Synchronous Generator using an Improved Unscented Kalman Filter Algorithm

Abstract

An enhanced Unscented Kalman Filter (UKF) technique for synchronous generator state estimation is presented in this study. The suggested approach overcomes the drawbacks of conventional UKF in managing noise and nonlinearities in power systems. Comparative analysis and validation are made on the tracking performance of Normal Ukf and Improved Ukf (SR-Ukf) algorithms and the simulation results show that, under the same conditions. The Normal UKF produced an RMSE of 0.5390, while the SR UKF achieved a markedly lower RMSE of 0.1540. corresponding to a 71.4% reduction in estimation error. According to simulation results, the enhanced UKF estimates generator states under a range of operating scenarios with more accuracy and robustness.