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Experimental study of turbulence intensity influence on wind turbine performance and wake recovery in a low-speed wind tunnel

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  • Talavera, Miguel
  • Shu, Fangjun

Abstract

Regarding the issue of the unmatched Reynolds number for down-scaled wind turbine tests, an experimental study of a single model wind turbine and an array with two turbines was performed under laminar and turbulent inflow conditions. Turbulent inflow was created using an active grid system installed between the contraction and test-section of the wind tunnel; the maximum turbulence intensity can reach 20%. Velocity fields upstream and in the wake of the turbine were measured using a 2D-PIV system. In the experiments with a single turbine, it was found that the power coefficient was strongly dependent on the inflow turbulence intensity, because turbulence influenced the flow separation in the suction side of the wind turbine blade. This was confirmed by PIV results taken under laminar and turbulent inflow conditions. For the wind turbine array case, the efficiency of both turbines was highly related to the turbulence intensity in the inflow. Furthermore, inflow turbulence intensity also influenced the wake recovery. The power coefficient of the wind turbines was similar to design value under controlled inflow turbulence. In conclusion, despite the unmatched Reynolds number, a realistic flow similar to the field can be reached using turbulent inflow created by an active grid system.

Suggested Citation

  • Talavera, Miguel & Shu, Fangjun, 2017. "Experimental study of turbulence intensity influence on wind turbine performance and wake recovery in a low-speed wind tunnel," Renewable Energy, Elsevier, vol. 109(C), pages 363-371.
    • Handle: RePEc:eee:renene:v:109:y:2017:i:c:p:363-371
    DOI: 10.1016/j.renene.2017.03.034
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    1. Singh, Ronit K. & Ahmed, M. Rafiuddin, 2013. "Blade design and performance testing of a small wind turbine rotor for low wind speed applications," Renewable Energy, Elsevier, vol. 50(C), pages 812-819.
    2. Pookpunt, Sittichoke & Ongsakul, Weerakorn, 2013. "Optimal placement of wind turbines within wind farm using binary particle swarm optimization with time-varying acceleration coefficients," Renewable Energy, Elsevier, vol. 55(C), pages 266-276.
    3. Hirahara, Hiroyuki & Hossain, M. Zakir & Kawahashi, Masaaki & Nonomura, Yoshitami, 2005. "Testing basic performance of a very small wind turbine designed for multi-purposes," Renewable Energy, Elsevier, vol. 30(8), pages 1279-1297.
    4. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2013. "Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions," Renewable Energy, Elsevier, vol. 52(C), pages 273-282.
    5. Lanzafame, R. & Mauro, S. & Messina, M., 2013. "Wind turbine CFD modeling using a correlation-based transitional model," Renewable Energy, Elsevier, vol. 52(C), pages 31-39.
    6. Adaramola, M.S. & Krogstad, P.-Å., 2011. "Experimental investigation of wake effects on wind turbine performance," Renewable Energy, Elsevier, vol. 36(8), pages 2078-2086.
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