Abstract & Details
Description
Award ID: 2437233
The broader/commercial impact of this Small Business Technology Transfer Research (STTR) Phase II project is to improve the efficiency and profitability of wind farms by reducing the losses caused by wake effectsareas of reduced wind speed and increased turbulence that form behind operating wind turbines. These wake effects lead to lower energy production, greater wear on turbines, and increased maintenance costs. The project aims to demonstrate a novel method of wind farm control known as wake steering, in which upstream turbines are deliberately misaligned to divert airflow around downstream turbines. This method could significantly increase the total energy output of a wind farm without requiring new hardware. If successful, the project will reduce the cost of wind energy, improve its reliability, and support clean, renewable power. These improvements will have wide-reaching benefits for the U.S. economy and environment, including the creation of high-value jobs and a reduction in reliance on fossil fuels. This project is based on a novel yaw control method called Log-of-Power Extremum Seeking Control (LP-ESC), a model-free feedback algorithm that adjusts turbine yaw angles in real time to maximize total wind farm power output. Unlike traditional model-based wake steering approaches, LP-ESC does not rely on detailed physical models of wake transport, which can be inaccurate, difficult to calibrate, and sensitive to atmospheric variability. The core innovation is an accelerated version of LP-ESC that converges quickly with minimal system dithering, minimizing added wear to turbines. The project will refine this algorithm, implement it on a programmable controller, and perform a field demonstration at a commercial wind farm using utility-scale turbines. Performance will be evaluated based on both power gains and mechanical load impacts. A successful demonstration will validate the technical feasibility and commercial potential of deploying a universal, retrofit-friendly wake steering system to increase energy output from existing wind farms. 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: Rajesh Mehta
The broader/commercial impact of this Small Business Technology Transfer Research (STTR) Phase II project is to improve the efficiency and profitability of wind farms by reducing the losses caused by wake effectsareas of reduced wind speed and increased turbulence that form behind operating wind turbines. These wake effects lead to lower energy production, greater wear on turbines, and increased maintenance costs. The project aims to demonstrate a novel method of wind farm control known as wake steering, in which upstream turbines are deliberately misaligned to divert airflow around downstream turbines. This method could significantly increase the total energy output of a wind farm without requiring new hardware. If successful, the project will reduce the cost of wind energy, improve its reliability, and support clean, renewable power. These improvements will have wide-reaching benefits for the U.S. economy and environment, including the creation of high-value jobs and a reduction in reliance on fossil fuels. This project is based on a novel yaw control method called Log-of-Power Extremum Seeking Control (LP-ESC), a model-free feedback algorithm that adjusts turbine yaw angles in real time to maximize total wind farm power output. Unlike traditional model-based wake steering approaches, LP-ESC does not rely on detailed physical models of wake transport, which can be inaccurate, difficult to calibrate, and sensitive to atmospheric variability. The core innovation is an accelerated version of LP-ESC that converges quickly with minimal system dithering, minimizing added wear to turbines. The project will refine this algorithm, implement it on a programmable controller, and perform a field demonstration at a commercial wind farm using utility-scale turbines. Performance will be evaluated based on both power gains and mechanical load impacts. A successful demonstration will validate the technical feasibility and commercial potential of deploying a universal, retrofit-friendly wake steering system to increase energy output from existing wind farms. 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: Rajesh Mehta
| Status | Active |
|---|---|
| Effective start/end date | 09/15/25 → 08/31/27 |
Lead and Sub-Awardee Organization(s)
Funding
- STTR Phase II: $1,246,771.00
Active Fiscal Year
- FY2027
- FY2026
- FY2025
Start Fiscal Year
- FY2025
TIP Programs
- STTR Phase II
Small Business
- Yes
Key Technology Areas
- Advanced Energy and Industrial Efficiency Technologies
- (confidence score: 100%)
Technology Foci
- Advanced Energy Generation Technologies
- (confidence score: 100%)
Congressional District at Award
- District n. 02 of Rhode Island
Current Congressional District
- District n. 02 of Rhode Island
United States
- Rhode Island
Core Based Statistical Area (CBSA)
- Providence-Warwick, RI-MA
County
- County: Washington, RI
EPSCoR Jurisdiction
- Yes
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