Complex-Phase, Data-Driven Identification of Grid-Forming Inverter Dynamics

Fuente: arXiv
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Main Authors: Büttner, Anna, Würfel, Hans, Liemann, Sebastian, Schiffer, Johannes, Hellmann, Frank
Format: Preprint
Published: 2024
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author Büttner, Anna
Würfel, Hans
Liemann, Sebastian
Schiffer, Johannes
Hellmann, Frank
author_facet Büttner, Anna
Würfel, Hans
Liemann, Sebastian
Schiffer, Johannes
Hellmann, Frank
contents The increasing integration of renewable energy sources (RESs) into power systems requires the deployment of grid-forming inverters to ensure a stable operation. Accurate modeling of these devices is necessary. In this paper, a system identification approach to obtain low-dimensional models of grid-forming inverters is presented. The proposed approach is based on a Hammerstein-Wiener parametrization of the normal-form model. The normal-form is a gray-box model that utilizes complex frequency and phase to capture non-linear inverter dynamics. The model is validated on two well-known control strategies: droop-control and dispatchable virtual oscillators. Simulations and hardware-in-the-loop experiments demonstrate that the normal-form accurately models inverter dynamics across various operating conditions. The approach shows great potential for enhancing the modeling of RES-dominated power systems, especially when component models are unavailable or computationally expensive.
format Preprint
id arxiv_https___arxiv_org_abs_2409_17132
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Complex-Phase, Data-Driven Identification of Grid-Forming Inverter Dynamics
Büttner, Anna
Würfel, Hans
Liemann, Sebastian
Schiffer, Johannes
Hellmann, Frank
Systems and Control
The increasing integration of renewable energy sources (RESs) into power systems requires the deployment of grid-forming inverters to ensure a stable operation. Accurate modeling of these devices is necessary. In this paper, a system identification approach to obtain low-dimensional models of grid-forming inverters is presented. The proposed approach is based on a Hammerstein-Wiener parametrization of the normal-form model. The normal-form is a gray-box model that utilizes complex frequency and phase to capture non-linear inverter dynamics. The model is validated on two well-known control strategies: droop-control and dispatchable virtual oscillators. Simulations and hardware-in-the-loop experiments demonstrate that the normal-form accurately models inverter dynamics across various operating conditions. The approach shows great potential for enhancing the modeling of RES-dominated power systems, especially when component models are unavailable or computationally expensive.
title Complex-Phase, Data-Driven Identification of Grid-Forming Inverter Dynamics
topic Systems and Control
url https://arxiv.org/abs/2409.17132