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Near-wake Flow Dynamics of a Horizontal Axis Wind Turbine

Download or Read eBook Near-wake Flow Dynamics of a Horizontal Axis Wind Turbine PDF written by Pooyan Hashemi Tari and published by . This book was released on 2012 with total page 282 pages. Available in PDF, EPUB and Kindle.
Near-wake Flow Dynamics of a Horizontal Axis Wind Turbine
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Total Pages : 282
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ISBN-10 : OCLC:1067245662
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Book Synopsis Near-wake Flow Dynamics of a Horizontal Axis Wind Turbine by : Pooyan Hashemi Tari

Book excerpt: Experiments have been conducted in a large wind tunnel set-up in order to study the flow structures within the near-wake region of a horizontal axis wind turbine. Particle Image Velocimetry (PIV) has been employed to quantify the mean and turbulent components of the flow field. The measurements have been performed in multiple adjacent horizontal planes in order to cover the area behind the rotor in a large radial interval, at several locations downstream of the rotor. The measurements were phase-locked in order to facilitate the re-construction of the three-dimensional flow field. Acquiring uniform particle distribution in the measurement planes as well as proper calibration for the process of patching the adjacent measurement planes were the major issues influencing the PIV measurements. The results demonstrate the successful implementation of the PIV technique and the associated post-processing to accurately construct the flow field in the near-wake of a HAWT in a large wind tunnel setup. The mean velocity and turbulence characteristics clearly correlate with the near-wake vortex dynamics and in particular with the helical structure of the flow, formed shortly behind the turbine rotor. The radial velocity is low at the mid section of the blade and increases towards the tip. Close to the rotor and close to the blade tip and root regions the mean and turbulent characteristics of the flow are highly dependent on the azimuth angle of blade due to the tip and root vortices. Further from the rotor, the characteristics of the flow become phase independent. This can be attributed to the breakdown of the vortical structure of the flow, resulting from the turbulent diffusion. In general, the highest levels of turbulence are observed in shear layer around the tip of the blades, which decrease rapidly downstream. The shear zone grows in the radial direction as the iv wake moves axially, resulting in velocity recovery toward the centre of the rotor due to momentum transport. These findings are important in wind farm studies, where it is essential to determine the region of influence of the wake of each wind turbine, to study the interaction of wind turbines in the farm. The findings are also significant, as they point out that in the far wake region, the turbulent characteristics are independent of azimuth angle of the blade, which suggests the possibility of generating simple and robust wind turbine wake models for wind farm analysis. In addition to quantification of mean and turbulent velocity field, the capability and limitation of the Blade Element Momentum (BEM) method in predicting axial velocity profiles at the location of the rotor disc has been assessed. For this purpose, the profiles obtained from PIV measurements have been compared with those acquired from the classical BEM method, as well as with the improved method which involves series of corrections, including tip loss, stall delay and thrust coefficient corrections. In general, the comparison shows good qualitative agreement between velocity profiles obtained from PIV measurements and those obtained by BEM method, when the corrections are applied. Moreover, the PIV results have also been compared with the results obtained from the velocity measurements performed by previous investigators in small wind tunnel set-ups, in order to assess the scaling effects, and in particular the effect of local chord Reynolds number. The tip speed ratio is considered to be similar for all measurement to satisfy the kinematic similarity requirement. The comparison shows that the axial velocity profiles are highly dependent on Reynolds number. This is an important finding in terms of simulating scaled models of wind turbines and wind farms in wind tunnel settings.


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