SBIR/STTR Research Award

Low-cost Lidar for Efficient Wind Energy Production

Award identifier b85fd9597fd5660f07b83e2ade81d3d97e4b4fd66c3da1a09683044345f1bcc0Awarding agency Department of Energy

Award amount

$199,832

Program and phase

SBIR · Phase I

Award year

2023

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
BOULDER NONLINEAR SYSTEMS, INC.
Proposal award date
2023-07-10
Contract end date
2024-04-09
UEI
N8J7GS1DB3A6
Solicitation number
DE-FOA-0002903
Topic code
C56-17a

Research abstract

C56-17a-273634Wind energy is becoming one of the least expensive resources for producing electricity when compared to building new plants to provide electricity from nuclear, coal, oil or gas. According to Forbes, this is true even for unsubsidized wind power plants and indicates that the ever-increasing need for electricity will be fulfilled in part by increasing or expanding land and offshore wind power stations. As with any limited resource, the best strategy is to efficiently extract all the available energy to reduce production cost and environmental impact. One method for improving the efficiency of wind turbines is to provide real-time control of the turbine to correct for YAW and blade error such that there is a more productive interaction with the wind field. Real-time control can be provided using 3D lidar mounted on the turbine to measure and characterize the approaching wind field. This data is used by the turbine to adjust to the incoming wind and optimize its energy production. If the lidar provides enough resolution across the wind field, it can also be used to detect damaging turbulence allowing the turbine to minimize its interaction and thus reduce repair and maintenance costs. For this type of real time control to be fully deployed, the cost of 3D wind lidar and its maintenance needs to substantially come down. This proposal describes a method for reducing unit cost and maintenance of nacelle-mounted 3D lidar systems by using a unique non-mechanical scanning technology, which simplifies the lidar’s optical system without compromising lidar performance. This scanning technology is currently being developed for lidar systems used in autonomous cars to reduce cost and improve reliability.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

111 SBIR/STTR records share this UEI (1989–2023). Reported award amounts total $34,997,508. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, Department of Commerce, National Science Foundation, Department of Agriculture

Agency intelligence

Department of Energy

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.