The Gaussian noise distribution is typically used in dynamic state estimation (DSE) but it is
not always true in practice because of abnormal system inputs, impulsive noise and …

Uncertainties such as abnormal system inputs, strong model nonlinearities, outliers and
impulsive noise unavoidably exist in the power system dynamic state estimation (SE)(DSE) …

Even though the noise model applied in power system dynamic state estimation (DSE) is
usually assumed to be Gaussian, this is not the case due to the unknown system inputs …

In realistic power system state estimation, the distribution of measurement noise is usually
assumed to be Gaussian while many researcher have verified that it can be non-Gaussian …

In practical applications like power system, the distribution of the measurement noise is
unknown or frequently deviates from the assumed Gaussian model, often being …

The traditional unscented Kalman filter (UKF) with mean square error (MSE) criterion for
dynamic state estimation (DSE) is sensitive for unknown non-Gaussian noise and outliers …

Due to the unfavorable interference of non-Gaussian noise, abnormal system states, and
rough measurement errors, dynamic state estimation (DSE) plays an important role in the …

Background: The state estimation (SE) process in power systems estimates bus voltage
magnitude and phase angles vital for operating the system securely and reliably. The power …

Dynamic state estimation (DSE) for generators plays an important role in power system
monitoring and control. Phasor measurement unit (PMU) has been widely utilized in DSE …

This paper develops an adaptive robust cubature Kalman filter (ARCKF) that is able to
mitigate the adverse effects of the innovation and observation outliers while filtering out the …