Application of a Robust Algorithm for Dynamic State Estimation of a Power System

Dynamic State Estimator Based on Wide Area Measurement System During Power System Electromechanical Transient Process

“…Comparing with the steady state estimation, the traditional dynamic state estimation [12][13][14][15] aims at the relative slow load fluctuation, which is different with the proposed dynamic state estimation during electromechanical transient process. The traditional dynamic state estimation employs the measurement equations based on the network constraints, and predicts the state variables using exponential smoothing techniques.…”

Distribution system state estimation-A step towards smart grid

“…From the literature, it can be observed that the DSE or FASE techniques are more focused on TSs, such as the studies done in [67,71] and [78]. In [67], an exponential-weight function is used to increase the robustness of the EKF-based estimator.…”

“…In [67], an exponential-weight function is used to increase the robustness of the EKF-based estimator. Another modification to this algorithm is given in [69], in which the Taylor's series of the non-linear measurement function is expanded to include the second order term, which enhances the accuracy of the estimation process.…”

Detection of Voltage Sag using An Adaptive Extended Kalman Filter Based on Maximum Likelihood

“…For example, considering the uncertainty of the process noise covariance matrix, Yu [10] proposed an adaptive Kalman filter method in which two basic Q models can be switched for steadystate and transient estimation. As a comparison, Shih and Huang [11] adjusted the measurement noise parameter R instead of Q to increase the robustness of the EKF method. For accurate analysis of harmonic content and fundamental frequency, Kennedy [12] employed an adaptive KF algorithm by adopting a methodical approach to choosing the noise covariance matrices R and Q simultaneously.…”