A Study on State Estimation of Synchronous Generator using an ImprovedUnscented Kalman Filter Algorithm
Keywords:
Improved UKF Algorithm, Nonlinear Filtering, Power Systems, State Estimation, Synchronous Generators,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.