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This content will become publicly available on December 23, 2026

Title: A Novel Discrete-Time State-Space Model for Decentralized Dynamic State Estimation of Grid-Forming Inverters
Stiff dynamics continue to pose challenges for power system dynamic state estimation. In particular, models of inverters with control schemes designed to support grid voltage and frequency, namely, grid-forming inverters (GFMs), are highly prone to numerical instability. This paper develops a novel analytical modeling technique derived from two cascading subsystems, namely synchronization and dq-frame voltage control. This allows us to obtain a closed-form discrete-time state-space model based on the matrix exponential function. The resulting model enables a numerically stable and decentralized dynamic state estimator that can track the dynamics of GFMs at standard synchrophasor reporting rates. In contrast, existing dynamic state estimators are subject to numerical issues. The proposed algorithm is tested on a 14-bus power system with a GFM and compared with the standard algorithm whose process model is discretized using well-known Runge-Kutta methods. Numerical results demonstrate the superiority of the proposed method under various conditions.  more » « less
Award ID(s):
2328241 2550498
PAR ID:
10656427
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
IEEE Transactions on Power Systems
Date Published:
Journal Name:
IEEE Transactions on Power Systems
ISSN:
0885-8950
Page Range / eLocation ID:
1 to 14
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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