IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v70y2014icp62-77.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148114001815
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2014.03.034?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Veisi, Amin Allah & Shafiei Mayam, Mohammad Hossein, 2017. "Effects of blade rotation direction in the wake region of two in-line turbines using Large Eddy Simulation," Applied Energy, Elsevier, vol. 197(C), pages 375-392.
    2. 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.
    3. Asmuth, Henrik & Navarro Diaz, Gonzalo P. & Madsen, Helge Aagaard & Branlard, Emmanuel & Meyer Forsting, Alexander R. & Nilsson, Karl & Jonkman, Jason & Ivanell, Stefan, 2022. "Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements," Renewable Energy, Elsevier, vol. 191(C), pages 868-887.
    4. Thé, Jesse & Yu, Hesheng, 2017. "A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods," Energy, Elsevier, vol. 138(C), pages 257-289.
    5. Win Naung, Shine & Nakhchi, Mahdi Erfanian & Rahmati, Mohammad, 2021. "High-fidelity CFD simulations of two wind turbines in arrays using nonlinear frequency domain solution method," Renewable Energy, Elsevier, vol. 174(C), pages 984-1005.
    6. 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).
    7. 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.
    8. Liu, Xiaodong & Feng, Bo & Liu, Di & Wang, Yiming & Zhao, Haitao & Si, Yulin & Zhang, Dahai & Qian, Peng, 2022. "Study on two-rotor interaction of counter-rotating horizontal axis tidal turbine," Energy, Elsevier, vol. 241(C).
    9. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2024. "A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    10. 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).
    11. Lee, Hakjin & Lee, Duck-Joo, 2020. "Low Reynolds number effects on aerodynamic loads of a small scale wind turbine," Renewable Energy, Elsevier, vol. 154(C), pages 1283-1293.
    12. Deskos, Georgios & Laizet, Sylvain & Piggott, Matthew D., 2019. "Turbulence-resolving simulations of wind turbine wakes," Renewable Energy, Elsevier, vol. 134(C), pages 989-1002.
    13. 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.
    14. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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).
    21. 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).
    22. Yang, Shanghui & Deng, Xiaowei & Yang, Kun, 2024. "Machine-learning-based wind farm optimization through layout design and yaw control," Renewable Energy, Elsevier, vol. 224(C).
    23. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yan, Chi & Archer, Cristina L., 2018. "Assessing compressibility effects on the performance of large horizontal-axis wind turbines," Applied Energy, Elsevier, vol. 212(C), pages 33-45.
    2. 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).
    3. 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.
    4. Veisi, Amin Allah & Shafiei Mayam, Mohammad Hossein, 2017. "Effects of blade rotation direction in the wake region of two in-line turbines using Large Eddy Simulation," Applied Energy, Elsevier, vol. 197(C), pages 375-392.
    5. 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).
    6. Cheng, Zhi & Lien, Fue-Sang & Yee, Eugene & Meng, Hang, 2022. "A unified framework for aeroacoustics simulation of wind turbines," Renewable Energy, Elsevier, vol. 188(C), pages 299-319.
    7. Ma, Hongliang & Ge, Mingwei & Wu, Guangxing & Du, Bowen & Liu, Yongqian, 2021. "Formulas of the optimized yaw angles for cooperative control of wind farms with aligned turbines to maximize the power production," Applied Energy, Elsevier, vol. 303(C).
    8. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
    9. Rubel C. Das & Yu-Lin Shen, 2023. "Analysis of Wind Farms under Different Yaw Angles and Wind Speeds," Energies, MDPI, vol. 16(13), pages 1-19, June.
    10. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Experimental investigation of the performance and wake effect of a small-scale wind turbine in a wind tunnel," Energy, Elsevier, vol. 166(C), pages 819-833.
    11. Sarlak, H. & Nishino, T. & Martínez-Tossas, L.A. & Meneveau, C. & Sørensen, J.N., 2016. "Assessment of blockage effects on the wake characteristics and power of wind turbines," Renewable Energy, Elsevier, vol. 93(C), pages 340-352.
    12. 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.
    13. Hayat, Imran & Chatterjee, Tanmoy & Liu, Huiwen & Peet, Yulia T. & Chamorro, Leonardo P., 2019. "Exploring wind farms with alternating two- and three-bladed wind turbines," Renewable Energy, Elsevier, vol. 138(C), pages 764-774.
    14. Deskos, Georgios & Laizet, Sylvain & Piggott, Matthew D., 2019. "Turbulence-resolving simulations of wind turbine wakes," Renewable Energy, Elsevier, vol. 134(C), pages 989-1002.
    15. Li, Qing'an & Cai, Chang & Kamada, Yasunari & Maeda, Takao & Hiromori, Yuto & Zhou, Shuni & Xu, Jianzhong, 2021. "Prediction of power generation of two 30 kW Horizontal Axis Wind Turbines with Gaussian model," Energy, Elsevier, vol. 231(C).
    16. Martin Robinius & Alexander Otto & Konstantinos Syranidis & David S. Ryberg & Philipp Heuser & Lara Welder & Thomas Grube & Peter Markewitz & Vanessa Tietze & Detlef Stolten, 2017. "Linking the Power and Transport Sectors—Part 2: Modelling a Sector Coupling Scenario for Germany," Energies, MDPI, vol. 10(7), pages 1-23, July.
    17. Khadijah Barashid & Amr Munshi & Ahmad Alhindi, 2023. "Wind Farm Power Prediction Considering Layout and Wake Effect: Case Study of Saudi Arabia," Energies, MDPI, vol. 16(2), pages 1-22, January.
    18. Luo, Kun & Zhang, Sanxia & Gao, Zhiying & Wang, Jianwen & Zhang, Liru & Yuan, Renyu & Fan, Jianren & Cen, Kefa, 2015. "Large-eddy simulation and wind-tunnel measurement of aerodynamics and aeroacoustics of a horizontal-axis wind turbine," Renewable Energy, Elsevier, vol. 77(C), pages 351-362.
    19. Guillem Armengol Barcos & Fernando Porté-Agel, 2023. "Enhancing Wind Farm Performance through Axial Induction and Tilt Control: Insights from Wind Tunnel Experiments," Energies, MDPI, vol. 17(1), pages 1-20, December.
    20. Deepu Dilip & Fernando Porté-Agel, 2017. "Wind Turbine Wake Mitigation through Blade Pitch Offset," Energies, MDPI, vol. 10(6), pages 1-17, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:70:y:2014:i:c:p:62-77. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.