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Research Papers

Novel Experimental Power Curve Determination and Computational Methods for the Performance Analysis of Vertical Axis Wind Turbines

[+] Author and Article Information
Jonathan M. Edwards

Department of Mechanical Engineering,  University of Sheffield, S1 3JD, Sheffield, United Kingdomj.m.edwards@sheffield.ac.uk

Louis Angelo Danao

Department of Mechanical Engineering,  University of Sheffield, S1 3JD, Sheffield, United Kingdom; Assistant Professor Department of Mechanical Engineering,  University of the Philippines, Diliman 1101, Quezon City, Philippineslouis.danao@sheffield.ac.uk

Robert J. Howell

Lecturer in Experimental Aerodynamics Department of Mechanical Engineering,  University of Sheffield, S1 3JD, Sheffield, United Kingdomr.howell@sheffield.ac.uk

J. Sol. Energy Eng 134(3), 031008 (May 07, 2012) (11 pages) doi:10.1115/1.4006196 History: Received June 30, 2011; Revised February 08, 2012; Published May 07, 2012; Online May 07, 2012

Through novel experimental and computational methods, this paper details a study into the performance aerodynamics of a small-scale vertical axis wind turbine (VAWT). A novel experimental method is first developed and validated before the results are compared to those of a computational fluid dynamics (CFD) study. The computational study is further validated by comparing the flow field to PIV data. The CFD simulations are then analyzed to explain the aerodynamics in further detail, including a discussion of the effect of the streamwise induction on the local angle of attack on the blade. The University of Sheffield’s three-bladed NACA0022 small-scale VAWT experimental rig is mounted within the University’s Low-Speed Wind Tunnel. Tests at tip speed ratios up to 5 were carried out, where the blade Reynolds number (based on rotational speed) ranged from 37,500 to 75,000. The same test conditions are simulated using unsteady computational fluid dynamics.

Copyright © 2012 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Plot showing effect of spin-down rate on Cp measurement, where t is the time taken to spin-down from 900 rpm to 100 rpm in the original spin-down test

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Figure 2

Lift coefficient loops for SST k-ω, RNG k-ε, S-A, and SST k-ω LR as compared to experiment results from Ref. [12]

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Figure 3

Streamlines for different angles of attack from Ref. [12] ((a) 16.75 deg↑, (c) 21.9 deg↑, (e) 24.7 deg↑, (g) 14.1 deg↓). (b), (d), (f), and (h) are numerical results for SST k-ω contours of vorticity

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Figure 4

Blade mesh and outer domain mesh

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Figure 5

Sketch showing setup for PIV equipment around working section, the laser sheet position is shown

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Figure 6

Cp variation with tip speed ratio as determined for experimental measurements and CFD simulations, at a wind speed of 6.57 m/s

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Figure 7

Kirke’s investigation [15] showing the effect of low Reynolds number performance on the shape of the Cp -λ curve

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Figure 8

Field of view of the camera at different azimuth positions

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Figure 9

Comparison of experimental and computational flow fields showing the upwind stalling process at λ  = 2.13 (gray areas are shadow regions)

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Figure 10

Comparison of experimental and computational flow fields showing the downwind stalling process at λ = 2.13 (gray areas are shadow regions)

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Figure 11

Velocity magnitude contour plot with streamlines at λ = 4.26: (a) instantaneous and (b) average

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Figure 12

Phases in the interpolation process for u at λ = 4.26: (a) average flow field, (b) cut–out step, and (c) interpolated flow field

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Figure 13

Velocity vector diagram for a VAWT blade for geometric angle of attack (left) and corrected angle of attack (right)

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Figure 14

Corrected α: (a) for λ = 4.26 versus geometric α (αss is the maximum steady α), (b) versus mathematical model predictions

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Figure 15

Torque components of lift and drag for λ = 4.26

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Figure 16

Forces on a blade for λ = 4.26

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Figure 17

Drag force on one blade for λ = 4.26

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