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.
@article{arxiv.1703.03374,
title = {PMU-Based Estimation of Dynamic State Jacobian Matrix},
author = {Xiaozhe Wang and Konstantin Turitsyn},
journal= {arXiv preprint arXiv:1703.03374},
year = {2017}
}
Comments
IEEE International Conference on Circuits and Systems (ISCAS) 2017