IR thermographic flow visualization for the quantification of boundary layer flow disturbances due to the leading edge condition

Christoph Dollinger, Nicholas Balaresque, Nicholas Gaudern, Daniel Gleichauf, Michael Sorg and Andreas Fischer

Renewable Energy, 2019, vol. 138, issue C, 709-721

Abstract: The aerodynamic performance of wind turbine rotor blades is influenced by the leading edge condition. Contamination and erosion cause increased surface roughness, unevenness or defects, which affect the boundary layer flow and, thus, reduce lift and increase drag. Current approaches used to determine the disturbed boundary layer flow are based on invasive flow probes with limited spatial resolution; therefore, a non-invasive, camera-based measurement of the boundary layer flow disturbances on wind turbines in operation is proposed using thermographic flow visualization. The actual and the undisturbed laminar-turbulent transition positions are determined in the thermographic images and a subsequent assignment to the rotor blade geometry obtains chord-based information. The normalized difference of both transition positions can be used as a metric to describe the extent of the disturbed boundary layer flow. The approach is demonstrated on a multi-MW horizontal axis wind turbine with a laminar flow reduction of up to 90.4 %. Furthermore, the measurement results allow the estimation of the annual energy production loss due to the leading edge condition, which enhances the industrial standard of simply comparing clean and tripped aerodynamic polars. For the investigated wind turbine, the annual energy production loss amounts to 4.7 % at 6 m/s average wind speed.

Keywords: IR thermographic flow visualization; Boundary layer measurement; Wind turbine rotor blades; Leading edge contamination; Leading edge erosion; Annual energy production (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:138:y:2019:i:c:p:709-721

DOI: 10.1016/j.renene.2019.01.116

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