Complex-Phase, Data-Driven Identification of Grid-Forming Inverter Dynamics
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909672639823872 |
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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 |