Non-steady wind turbine response to daytime atmospheric turbulence
Relevant to drivetrain bearing fatigue failures, we analyse non-steady wind turbine responses from interactions between energy-dominant daytime atmospheric turbulence eddies and the rotating blades of a GE 1.5 MW wind turbine using a unique dataset from a GE field experiment and computer simulation. Time-resolved local velocity data were collected at the leading and trailing edges of an instrumented blade together with generator power, revolutions per minute, pitch and yaw. Wind velocity and temperature were measured upwind on a meteorological tower. The stability state and other atmospheric conditions during the field experiment were replicated with a large-eddy simulation in which was embedded a GE 1.5 MW wind turbine rotor modelled with an advanced actuator line method. Both datasets identify three important response time scales: advective passage of energy-dominant eddies (≈25–50 s), blade rotation (once per revolution (1P), ≈3 s) and sub-1P scale (<1 s) response to internal eddy structure. Large-amplitude short-time ramp-like and oscillatory load fluctuations result in response to temporal changes in velocity vector inclination in the aerofoil plane, modulated by eddy passage at longer time scales. Generator power responds strongly to large-eddy wind modulations. Lastly, we show that internal dynamics of the blade boundary layer near the trailing edge is temporally modulated by the non-steady external flow that was measured at the leading edge, as well as blade-generated turbulence motions.
- Research Organization:
- Pennsylvania State Univ., University Park, PA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
- Grant/Contract Number:
- EE0005481
- OSTI ID:
- 1348834
- Journal Information:
- Philosophical Transactions of the Royal Society. A, Mathematical, Physical and Engineering Sciences, Vol. 375, Issue 2091; ISSN 1364-503X
- Publisher:
- The Royal Society PublishingCopyright Statement
- Country of Publication:
- United States
- Language:
- English
A Text-Mining Approach to Assess the Failure Condition of Wind Turbines Using Maintenance Service History
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journal | May 2019 |
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