Investigating the capabilities of virtual synchronous machines to provide instantaneous reserve in a laboratory environment
The increasing integration of renewable energy sources poses significant challenges to grid stability due to reduced system inertia traditionally provided by synchronous generators. This study evaluates the performance of grid-forming (GFM) and grid-following (GFL) inverter control strategies in providing virtual inertia to stabilize frequency in distribution networks. A Virtual Synchronous Machine (VSM) is benchmarked against GFM and GFL droop controls using laboratory experiments that simulate frequency and load disturbances. The results demonstrate that GFM strategies, particularly the VSM, deliver rapid active power responses, outperforming the delayed dynamics of GFL controls. The VSM's ability to emulate inertia significantly mitigates frequency nadirs and stabilizes the grid during transient events. Transfer function analysis highlights the second-order dynamics of the VSM, revealing that parameters such as inertia constant and static gain critically influence transient and steady-state performance. Larger inertia constants enhance frequency stabilization but introduce overshoot and oscillations, requiring precise parameter tuning to achieve a balance between stability and responsiveness. The findings emphasize the potential of GFM controls, especially VSM, in enhancing grid stability in low-inertia, renewable-heavy networks. Future research aims to explore coordinated multi-inverter control frameworks to further optimize grid-wide stability and resilience.
Authors
- Alexander Winkens (ORCID: https://orcid.org/0000-0002-6640-3692)
- Mahmood Kharrat
- Andreas Ulbig (ORCID: https://orcid.org/0000-0001-5834-1842)
- Irina Zettl (ORCID: https://orcid.org/0009-0007-8611-1383)
- Alexander Och
Institutions
- RWTH Aachen University (DE)
Publication Details
- Journal
- IET conference proceedings.
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1049/icp.2025.1740
- Primary Topic
- Experimental Learning in Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00