PMU-Based Estimation of Dynamic State Jacobian Matrix
For power system operators, this method enables near real-time estimation of system dynamics for stability monitoring and control, but it is an incremental improvement combining existing techniques.
The paper proposes a hybrid measurement and model-based method to estimate the dynamic state Jacobian matrix in near real-time, which is computationally efficient and robust to network topology changes. The method is demonstrated for online oscillation analysis, stability monitoring, and control, and can also approximate generator damping for model validation.
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. Since the estimated Jacobian matrix carries significant information on system dynamics and states, it can be utilized in various applications. In particular, two application of the estimated Jacobian matrix in online oscillation analysis, stability monitoring and control are illustrated with numerical examples. In addition, a side-product of the proposed method can facilitate model validation by approximating the damping of generators.