Grid impedance estimation based Kalman Filter
Abstract
Modern power systems face new operational hurdles due to the increasing adoption of inverter-coupled distributed energy resources, which impact system stability and control. Central to these challenges is the dynamic nature of grid impedance. To address this, a novel real-time estimation algorithm based on the Discrete Fourier Transform is proposed. This algorithm is embedded within an Advanced Angle Estimation Kalman Filter framework that employs a Linear Quadratic Regulator for current control (AAEKF-LQR). The impedance data directly informs and refines the controller's phase angle estimation. Simulation analyses demonstrate robust collaboration between the estimator and controller, sustaining system stability under weak grid conditions. The technique proves capable of delivering swift and accurate impedance updates during grid variations, which is crucial for maintaining stable inverter operation
Cite
@article{arxiv.2507.17325,
title = {Grid impedance estimation based Kalman Filter},
author = {Phuoc Sang Nguyen and Ghavameddin Nourbakhsh and Gerard Ledwich},
journal= {arXiv preprint arXiv:2507.17325},
year = {2025}
}
Comments
This paper has been withdrawn by the author because it does not include grid voltage estimation, which is essential for accurate grid impedance estimation. Additional validation and the application of appropriate methods for grid voltage estimation are required before the work can be finalised