Advertisement

The effect of tip speed ratio on a vertical axis wind turbine at high Reynolds numbers

  • Colin M. ParkerEmail author
  • Megan C. Leftwich
Research Article

Abstract

This work visualizes the flow surrounding a scaled model vertical axis wind turbine at realistic operating conditions. The model closely matches geometric and dynamic properties—tip speed ratio and Reynolds number—of a full-size turbine. The flow is visualized using particle imaging velocimetry (PIV) in the midplane upstream, around, and after (up to 4 turbine diameters downstream) the turbine, as well as a vertical plane behind the turbine. Time-averaged results show an asymmetric wake behind the turbine, regardless of tip speed ratio, with a larger velocity deficit for a higher tip speed ratio. For the higher tip speed ratio, an area of averaged flow reversal is present with a maximum reverse flow of \(-0.04U_\infty\). Phase-averaged vorticity fields—achieved by syncing the PIV system with the rotation of the turbine—show distinct structures form from each turbine blade. There were distinct differences in results by tip speed ratios of 0.9, 1.3, and 2.2 of when in the cycle structures are shed into the wake—switching from two pairs to a single pair of vortices being shed—and how they convect into the wake—the middle tip speed ratio vortices convect downstream inside the wake, while the high tip speed ratio pair is shed into the shear layer of the wake. Finally, results show that the wake structure is much more sensitive to changes in tip speed ratio than to changes in Reynolds number.

Keywords

Vortex Reynolds Number Particle Imaging Velocimetry Wind Tunnel Shear Layer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors wish to thank Matthew Glasstone and Allen Schultz for their experimental assistance. We thank Antonio Posa and Elias Balaras for much insightful discussion and many helpful suggestions. Thank you to The Metro Washington Chapter of the Achievement Rewards for College Students (ARCS) Foundation and the McNichols Foundation for their financial support of my education.

Supplementary material

Supplementary material 1 (mp4 9878 KB)

Supplementary material 2 (mp4 8516 KB)

Supplementary material 3 (mp4 4487 KB)

References

  1. Araya DB, Dabiri JO (2015) A comparison of wake measurements in motor-driven and flow-driven turbine experiments. Exp Fluids 56(7):1–15CrossRefGoogle Scholar
  2. Association AWE et al (2012) Awea us wind industry: first quarter 2012 market reportGoogle Scholar
  3. Barsky DA, Posa A, Rahromostaqim M, Leftwich M, Balaras E (2014) Experimental and computational wake characterization of a vertical axis wind turbine. American Institute of Aeronautics and Astronautics. doi: 10.2514/6.2014-3141
  4. Barthelmie RJ, Jensen L (2010) Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm. Wind Energy 13(6):573–586CrossRefGoogle Scholar
  5. Cal RB, Lebrón J, Castillo L, Kang HS, Meneveau C (2010) Experimental study of the horizontally averaged flow structure in a model wind-turbine array boundary layer. J Renew Sustain Energy 2(013):106Google Scholar
  6. Chan AS, Pa D, Jameson A, Liang C, Smits AJ (2011) Vortex suppression and drag reduction in the wake of counter-rotating cylinders. J Fluid Mech 679:343–382. doi: 10.1017/jfm.2011.134 CrossRefzbMATHGoogle Scholar
  7. Dabiri J (2011) Potential order-of-magnitude enhancement of wind farm power density via counter-rotating vertical-axis wind turbine arrays. J Renew Sustain Energy 3:043104. doi: 10.1063/1.3608170 CrossRefGoogle Scholar
  8. Grady S, Hussaini M, Abdullah MM (2005) Placement of wind turbines using genetic algorithms. Renew Energy 30(2):259–270CrossRefGoogle Scholar
  9. Grasso F, Ceyhan O (2014) Usage of advanced thick airfoils for the outer part of very large offshore turbines. J Phys Conf Ser. doi: 10.1088/1742-6596/524/1/012030
  10. Howell R, Qin N, Edwards J, Durrani N (2010) Wind tunnel and numerical study of a small vertical axis wind turbine. Renew Energy 35(2):412–422CrossRefGoogle Scholar
  11. Islam M, Ting D, Fartaj A (2008) Aerodynamic models for Darrieus-type straight-bladed vertical axis wind turbines. Renew Sustain Energy Rev 12(4):1087–1109. doi: 10.1016/j.rser.2006.10.023 CrossRefGoogle Scholar
  12. Karabelas S, Koumroglou B, Argyropoulos C, Markatos N (2012) High Reynolds number turbulent flow past a rotating cylinder. Appl Math Model 36:379–398MathSciNetCrossRefzbMATHGoogle Scholar
  13. Kinzel M, Mulligan Q, Dabiri JO (2013) Energy exchange in an array of vertical-axis wind turbines. J Turbul 13(38):1–13Google Scholar
  14. Mittal S, Kumar B (2003) Flow past a rotating cylinder. J Fluid Mech 476:303–334. doi: 10.1017/S0022112002002938 MathSciNetCrossRefzbMATHGoogle Scholar
  15. Paraschivoiu I (1981) Double-multiple streamtube model for Darrieus wind turbines. In: Second DOE/NASA wind turbines dynamics workshop. NASA CP-2186. Cleveland, OH, pp 19–25Google Scholar
  16. Posa A, Parker CM, Leftwich MC, Balaras E (2016) Wake structure of a single vertical axis wind turbine. Int J Heat Fluid Flow. doi: 10.1016/j.ijheatfluidflow.2016.02.002
  17. Strickland JH (1977) A performance prediction model for the darrieus turbine. In: International symposium on wind energy systems, vol 1Google Scholar
  18. Tescione G, Ragni D, He C, Ferreira CS, van Bussel G (2014) Near wake flow analysis of a vertical axis wind turbine by stereoscopic particle image velocimetry. Renew Energy 70:47–61CrossRefGoogle Scholar
  19. US Department of Energy (2008) 20 % wind energy by 2030. Tech. repGoogle Scholar
  20. Wilson RE, Lissaman PB (1974) Machines power wind of aerodynamics. Tech. rep., Oregon State University, Corvallis (USA)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Mechanical and Aerospace EngineeringThe George Washington UniversityWashingtonUSA

Personalised recommendations