PMU-Based Estimation of Dynamic State Jacobian Matrix

TL;DR

This paper introduces a hybrid measurement- and model-based approach for real-time estimation of the dynamic state Jacobian matrix, improving robustness and efficiency in power system monitoring.

Contribution

It presents a novel method that accurately estimates the Jacobian matrix in near real-time, outperforming traditional model-based methods during topology changes.

Findings

Accurately estimates the Jacobian matrix in near real-time.

Demonstrates robustness to network topology variations.

Outperforms existing model-based methods during undetectable topology changes.

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. 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.