Robust estimation method for power system dynamic synchronization with sensor gain degradation

Efficient and accurate real-time estimation of power system synchronization is quite important for its safety control and operation. However, signal sensing failure, electromagnetic interference, system delay, etc., will cause the sensor gain degradation. To furnish a dependable method for dynamic estimation in power grid synchronization amid sensor gain degradation, this research presents a robust estimation system capable of monitoring and tracking the frequency, voltage phase angles, and magnitudes. Firstly, the random degradation of measurement data is characterized by a discrete distribution within the range [0,1]. Secondly, the state space model of sensor gain degradation is established. Subsequently, a novel modified fault-tolerant extended Kalman filter (MFTEKF) is developed under the recursive estimator framework. Finally, extensive experimental results definitively demonstrate that the proposed MFTEKF can accurately monitor the dynamic characteristics of the power grid.