  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.
