PMU-Based Estimation of Dynamic State Jacobian Matrix

TL;DR

This paper introduces a hybrid measurement-model approach for real-time estimation of the dynamic state Jacobian matrix, enhancing system stability analysis and model validation in power systems.

Contribution

It presents a novel, efficient method for near real-time Jacobian matrix estimation that is robust to topology changes and useful for stability and oscillation analysis.

Findings

Accurately estimates Jacobian matrix in near real-time

Improves online oscillation analysis and stability monitoring

Facilitates generator damping estimation for model validation

Abstract

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.