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Blind Test 2 calculations for two in-line model wind turbines where the downstream turbine operates at various rotational speeds

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  • Pierella, Fabio
  • Krogstad, Per-Åge
  • Sætran, Lars

Abstract

In this paper we report on the results of the Blind Test 2 workshop, organized by Norcowe and Nowitech in Trondheim, Norway in October 2012. This workshop was arranged in order to find out how well wind turbine simulation models perform when applied to two turbines operating in line. Modelers with a suitable code were given boundary conditions of a wind tunnel test performed in the large wind tunnel facility at the Department of Energy and Process Engineering, at NTNU Trondheim, where two almost identical model turbines with a diameter of about 0.9∼m had been tested under various operating conditions. A detailed geometry specification of the models could be downloaded and the modelers were invited to submit the calculation without knowing the experimental results in advance.

Suggested Citation

  • Pierella, Fabio & Krogstad, Per-Åge & Sætran, Lars, 2014. "Blind Test 2 calculations for two in-line model wind turbines where the downstream turbine operates at various rotational speeds," Renewable Energy, Elsevier, vol. 70(C), pages 62-77.
    • Handle: RePEc:eee:renene:v:70:y:2014:i:c:p:62-77
    DOI: 10.1016/j.renene.2014.03.034
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    References listed on IDEAS

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    1. Wood, D.H., 1997. "Some effects of compressibility on small horizontal-axis wind turbines," Renewable Energy, Elsevier, vol. 10(1), pages 11-17.
    2. Krogstad, Per-Åge & Eriksen, Pål Egil, 2013. "“Blind test” calculations of the performance and wake development for a model wind turbine," Renewable Energy, Elsevier, vol. 50(C), pages 325-333.
    3. 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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    Cited by:

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    7. Deskos, Georgios & Laizet, Sylvain & Piggott, Matthew D., 2019. "Turbulence-resolving simulations of wind turbine wakes," Renewable Energy, Elsevier, vol. 134(C), pages 989-1002.
    8. Sarlak, H. & Meneveau, C. & Sørensen, J.N., 2015. "Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions," Renewable Energy, Elsevier, vol. 77(C), pages 386-399.
    9. Amin Allah, Veisi & Shafiei Mayam, Mohammad Hossein, 2017. "Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines," Energy, Elsevier, vol. 121(C), pages 533-544.
    10. Ti, Zilong & Deng, Xiao Wei & Zhang, Mingming, 2021. "Artificial Neural Networks based wake model for power prediction of wind farm," Renewable Energy, Elsevier, vol. 172(C), pages 618-631.
    11. Li, Siyi & Zhang, Mingrui & Piggott, Matthew D., 2023. "End-to-end wind turbine wake modelling with deep graph representation learning," Applied Energy, Elsevier, vol. 339(C).
    12. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    13. Syed Ahmed Kabir, Ijaz Fazil & Safiyullah, Ferozkhan & Ng, E.Y.K. & Tam, Vivian W.Y., 2020. "New analytical wake models based on artificial intelligence and rivalling the benchmark full-rotor CFD predictions under both uniform and ABL inflows," Energy, Elsevier, vol. 193(C).
    14. Eriksen, Pål Egil & Krogstad, Per-Åge, 2017. "Development of coherent motion in the wake of a model wind turbine," Renewable Energy, Elsevier, vol. 108(C), pages 449-460.
    15. Qian, Yaoru & Wang, Tongguang & Yuan, Yiping & Zhang, Yuquan, 2020. "Comparative study on wind turbine wakes using a modified partially-averaged Navier-Stokes method and large eddy simulation," Energy, Elsevier, vol. 206(C).
    16. Yang, Shanghui & Deng, Xiaowei & Ti, Zilong & Yan, Bowen & Yang, Qingshan, 2022. "Cooperative yaw control of wind farm using a double-layer machine learning framework," Renewable Energy, Elsevier, vol. 193(C), pages 519-537.
    17. He, Ruiyang & Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2022. "Wind tunnel tests for wind turbines: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    18. Kim, Joon-Hyung & Cho, Bo-Min & Kim, Sung & Kim, Jin-Woo & Suh, Jun-Won & Choi, Young-Seok & Kanemoto, Toshiaki & Kim, Jin-Hyuk, 2017. "Design technique to improve the energy efficiency of a counter-rotating type pump-turbine," Renewable Energy, Elsevier, vol. 101(C), pages 647-659.
    19. Stevens, Richard J.A.M. & Martínez-Tossas, Luis A. & Meneveau, Charles, 2018. "Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments," Renewable Energy, Elsevier, vol. 116(PA), pages 470-478.
    20. Elie, B. & Oger, G. & Vittoz, L. & Le Touzé, D., 2022. "Simulation of two in-line wind turbines using an incompressible Finite Volume solver coupled with a Blade Element Model," Renewable Energy, Elsevier, vol. 187(C), pages 81-93.
    21. Lignarolo, Lorenzo E.M. & Mehta, Dhruv & Stevens, Richard J.A.M. & Yilmaz, Ali Emre & van Kuik, Gijs & Andersen, Søren J. & Meneveau, Charles & Ferreira, Carlos J. & Ragni, Daniele & Meyers, Johan & v, 2016. "Validation of four LES and a vortex model against stereo-PIV measurements in the near wake of an actuator disc and a wind turbine," Renewable Energy, Elsevier, vol. 94(C), pages 510-523.

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