Abstract & Details
Description
Award ID: 2134840
Coordinated networked microgrids (NMs) promise to significantly enhance power grid reliability. Three main challenges prevent their wide adoption: 1) Lack of understanding of NM dynamics; 2) Big data but limited/unscalable analytics; 3) Cyber-infrastructure bottlenecks. This project aims to develop AI-Grid: AI-enabled, provably resilient NMs. Key innovations are a programmable platform integrating reliable modeling under uncertainty, reachability analysis, formal control, high-assurance software architectures, and cybersecurity technologies to enable scalable, autonomic, and ultra-resilient microgrids and NMs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Michael Reksulak
Coordinated networked microgrids (NMs) promise to significantly enhance power grid reliability. Three main challenges prevent their wide adoption: 1) Lack of understanding of NM dynamics; 2) Big data but limited/unscalable analytics; 3) Cyber-infrastructure bottlenecks. This project aims to develop AI-Grid: AI-enabled, provably resilient NMs. Key innovations are a programmable platform integrating reliable modeling under uncertainty, reachability analysis, formal control, high-assurance software architectures, and cybersecurity technologies to enable scalable, autonomic, and ultra-resilient microgrids and NMs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Michael Reksulak
| Status | Closed |
|---|---|
| Effective start/end date | 10/01/21 → 04/30/25 |
Lead and Sub-Awardee Organization(s)
Funding
- Other Programs (Technology): $5,000,000.00
Active Fiscal Year
- FY2024
- FY2023
- FY2022
- FY2025
Start Fiscal Year
- FY2022
TIP Programs
- Other Programs (Technology)
Key Technology Areas
- Artificial Intelligence
- (confidence score: 100%)
- Advanced Energy and Industrial Efficiency Technologies
- (confidence score: 100%)
- Data and Cybersecurity
- (confidence score: 98%)
Technology Foci
- Advanced Energy Generation Technologies
- (confidence score: 100%)
- Advanced Transmission and Distribution systems
- (confidence score: 100%)
- Autonomy
- (confidence score: 89%)
- Data and Cybersecurity (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 01 of New York
Current Congressional District
- District n. 01 of New York
United States
- New York
Core Based Statistical Area (CBSA)
- New York-Newark-Jersey City, NY-NJ
County
- County: Suffolk, NY
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