PMU-Based Estimation of Dynamic State Jacobian Matrix
For power system operators, this method provides a more robust and accurate estimation of the dynamic state Jacobian matrix, aiding in real-time monitoring and model validation.
The paper proposes a hybrid measurement- and model-based method to estimate the dynamic state Jacobian matrix in near real-time, demonstrating superior performance over model-based methods under undetectable network topology changes.
In this paper, a hybrid measurement- and model-based method is proposed which can estimate the dynamic state Jacobian matrix in near real-time. The proposed method is computationally efficient and robust to the variation of network topology. A numerical example is given to show that the proposed method is able to provide good estimation for the dynamic state Jacobian matrix and is superior to the model-based method under undetectable network topology change. The proposed method may also help identify big discrepancy in the assumed network model.