NSF award 2625248 · University of Denver

Physics-Grounded Deep Reinforcement Learning for Adaptive Out-of-Step Protection in Low-Inertia Power Grids

Final report due

28 November 2029

in 1,137 days · The award ends on 31 July 2029.

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PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Jul 2029in 1007 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 31 July 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 November 2029.

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Award card

Award number: 2625248
Period of support: 15 Aug 2026 – 31 Jul 2029
Amount: $314,144
Awardee: University of Denver, Denver, CO
Program: EPCL: Energy, Power, Control,
Directorate: ENG

Abstract

This NSF project aims to develop a physics-grounded artificial intelligence (AI) framework for power grid protection that keeps grids safe as they undergo rapid and fundamental change. A critical threat to grid reliability is the out-of-step (OOS) condition, where the loss of synchronization can cause permanent equipment damage and trigger cascading blackouts. As inverter-based resources grow and system inertia…

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