Weathervane - A Predictive Analytics Engine for Global Monitoring of Wind Turbines

Award Information
Agency:
Department of Energy
Branch
n/a
Amount:
$999,994.00
Award Year:
2011
Program:
SBIR
Phase:
Phase II
Contract:
DE-FG02-10ER85903
Award Id:
n/a
Agency Tracking Number:
94501
Solicitation Year:
2011
Solicitation Topic Code:
07 c
Solicitation Number:
DE-FOA-0000508
Small Business Information
MI, Suite B, Ann Arbor, MI, 48108-2285
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
969868298
Principal Investigator:
Erik Erlandson
Mr.
(734) 975-8777
eerlandson@michaero.com
Business Contact:
Peter Tchoryk
Mr.
(734) 975-8777
ptchoryk@michaero.com
Research Institution:
Stub




Abstract
As wind turbine rotor diameters increase in size, especially for offshore wind farms, susceptibility to damaging wind conditions is increasing as well. The fatigue and extreme loads that a turbine must endure ends up increasing the Cost of Energy (CoE) significantly through higher maintenance and repair costs, reduced availability, shorter lifetimes, and increased initial purchase cost because of the need for greater design margin. These problems are exacerbated for larger turbines and when major repairs require cranes to replace damaged components. Inefficiency is also a problem as wind turbines cannot anticipate wind speed or direction changes before they actually arrive at the turbine. This proposal introduces a new approach that combines unique CM software with Ultraviolet (UV) Lidar (Light Detection and Ranging) sensor. UV Lidar is a promising tool for measuring wind speed and direction hundreds of meters ahead of the turbine, providing advanced knowledge of wind conditions that can lead to damaging fatigue and extreme loads. It is proposed to combine condition monitoring output with forward looking Lidar data using a fault-tolerant control strategy. The condition of the turbine and advanced measurement of the wind flow field will then be used to determine an optimal solution for emergency, reconfigurable, or accommodating control. It is anticipated that these improved control decisions will lead to improvement in load reduction versus Lidar-based or CM approaches alone, ultimately resulting in longer lifetimes of critical turbine components and greater turbine availability. The Phase I project demonstrated the ability of the new CM software to detect faults in CM data from wind turbines. This showed the feasibility of the approach, attracting increased wind industry interest in the project. The CM software will continue to be developed as a product in its own right, but in Phase II will also be applied to fault-tolerant control. In Phase II, we will start by demonstrating the feasibility and effectiveness of integrating the CM software with UV Lidar wind measurements by modeling and simulation. Success at the modeling level will be followed by field testing the system, including UV Lidar, on a fully instrumented test turbine. Plans will be made to continue field testing on utility-scale turbines with our partners. We will also look specifically at offshore turbine requirements and benefits of the system. Commercial Applications and Other Benefits: This Phase II effort will help accelerate deployment of three types of commercial products: (1) a stand-alone CM software package that can improve fault prediction and lead to lower maintenance and improved turbine availability, (2) a combined CM, forward-looking UV Lidar, and fault-tolerant control system to help turbines avoid damaging wind conditions and increase lifetime, and (3) a unique forward-looking UV Lidar that can also be applied to turbine control for enhancing energy capture, as well as other wind energy applications, such as site assessment and forecasting. These products would address well-known needs in the wind industry. The benefits apply to a customer base that includes turbine OEMs, wind farm developers, and operators.

* information listed above is at the time of submission.

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