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

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/persons/resource/buettner

Büttner,  Anna
Potsdam Institute for Climate Impact Research;

/persons/resource/wuerfel.hans

Würfel,  Hans
Potsdam Institute for Climate Impact Research;

Liemann,  Sebastian
External Organizations;

Schiffer,  Johannes
External Organizations;

/persons/resource/frank.hellmann

Hellmann,  Frank       
Potsdam Institute for Climate Impact Research;

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Zitation

Büttner, A., Würfel, H., Liemann, S., Schiffer, J., Hellmann, F. (2025): Complex-Phase, Data-Driven Identification of Grid-Forming Inverter Dynamics. - IEEE Transactions on Smart Grid, 16, 6, 4854-4864.
https://doi.org/10.1109/TSG.2025.3591891


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_33457
Zusammenfassung
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.