ERI: Scalable Machine Learning Frameworks for Stability Enhancement in Inverter-Dominated — NSF Award to Regents of the University
This NSF ERI project aims to enhance the stability and resilience of modern power systems as they increasingly rely on inverter-based resources, such as distributed power generation and battery energy storage systems. While these technologies are essential for a sustainable energy future, they introduce fast and comple
| Award title | ERI: Scalable Machine Learning Frameworks for Stability Enhancement in Inverter-Dominated |
|---|---|
| Award ID | 2552448 |
| Awardee | Regents of the University of Michigan - Dearborn |
| City | Dearborn |
| State | MI |
| Amount obligated | $199,984 |
| Principal investigator | VAN HAI BUI |
| Program | ERI-Eng. Research Initiation |
| Start date | 06/01/2026 |
| Abstract | This NSF ERI project aims to enhance the stability and resilience of modern power systems as they increasingly rely on inverter-based resources, such as distributed power generation and battery energy storage systems. While these technologies are essential for a sustainable energy future, they introduce fast and complex dynamics that make power grids more difficult to monitor and control. Traditional analysis tools are no longer sufficient due to limited visibility into how these devices operate |
| Source | NSF Awards |
$799/mo
Try NSFGrants →