NSF award 2502019 · Wake Forest University

ERI: Toward Reliable Frequency Support by Wind Farms: A Physics-Informed Machine Learning Approach

Final report due

29 December 2027

in 437 days · The award ends on 31 August 2027.

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Decide about an extension3 May 2027in 197 days
award ending 2027-08-31 · Research.gov
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Extension request17 Jul 2027in 272 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Aug 2027in 307 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Dec 2027in 437 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Dec 2027in 437 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Dec 2027in 437 days
award ending 2027-08-31 · 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 August 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 December 2027.

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Award card

Award number: 2502019
Period of support: 1 Sep 2025 – 31 Aug 2027
Amount: $194,280
Awardee: Wake Forest University, Winston Salem, NC
Program: ERI-Eng. Research Initiation
Directorate: ENG

Abstract

Wind farms offer substantial environmental advantages but pose serious challenges to power grid stability due to the diminishing presence of synchronous generators' inertia. While a wind farm can offer virtual inertia and power reserve support via pitch de-loading, there has been no investigation into the effect on the turbines’ fatigue load. Further, forecasting an accurate wind power reserve is challenging,…

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