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Digital tuft analysis of stall on operational wind turbines
Authors:Nigel Swytink‐Binnema  David A. Johnson
Affiliation:Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
Abstract:Operational wind turbines are exposed to dynamic inflow conditions because of, for instance, atmospheric turbulence and wind shear. In order to understand the resulting three‐dimensional and transient aerodynamics effects at a site, a 10m stall‐regulated upwind two‐bladed wind turbine was instrumented for a novel digital tuft flow visualization study. High definition video of a tufted blade was acquired during wind turbine operation in the field, and a novel digital image processing algorithm calculated the blade stall directly from the video. After processing O(105) sequential images, the algorithm achieved a ?5% bias error compared with previous manual analysis methods. With increasing wind speed (5m/s to 20m/s) the fraction of tufts exhibiting stalled flow increased from 5% to 40% on the outboard 40% of the blade. The independently measured instantaneous turbine power production correlates highly with the stall fraction. Some azimuthal variation in the stall fraction associated with dynamic stall induced by vertical wind shear was seen with a maximum in the 45–90° azimuthal location. The high detail, quantitative image processing method demonstrated good agreement with the expected behaviour for a stall‐regulated wind turbine and revealed azimuthal variation because of shear‐induced dynamic stall. The amount of reliable blade stall data to be obtained from digital tuft visualization has hereby been vastly increased. Copyright © 2015 John Wiley & Sons, Ltd.
Keywords:aerodynamics  blade stall  dynamic stall  flow visualization  horizontal‐axis wind turbines  image processing
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