IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v116y2018ipap470-478.html
   My bibliography  Save this article

Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments

Author

Listed:
  • Stevens, Richard J.A.M.
  • Martínez-Tossas, Luis A.
  • Meneveau, Charles

Abstract

We compare wind farm large eddy simulations with the EPFL wind tunnel measurement by Chamorro and Porté-Agel (Bound-Lay. Meteorol. 136, 515 (2010) and Energies 4, 1916 (2011)). We find that the near turbine wake, up to 3 turbine diameters downstream, of a single turbine is captured better with the actuator line method than using the actuator disk method. Further downstream the results obtained with both models agrees very well with the experimental data, confirming findings from previous studies. For large aligned wind farms we find that the actuator disk model predicts the wake profiles behind turbines on the second and subsequent rows more accurately than the wake profile behind the first turbine row. The reason is that the wake layer profile that is created at hub height in very large wind farms is closer to the assumptions made in the actuator disk model than the logarithmic profile found in the inflow conditions. In addition, we show that, even in relatively coarse resolution simulations, adding the effect of the turbine nacelle and tower leads to a significant improvement in the prediction of the near wake features at 1 and 2 diameters downstream.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:116:y:2018:i:pa:p:470-478
    DOI: 10.1016/j.renene.2017.08.072
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117308339
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.08.072?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. 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.
    2. Wu, Yu-Ting & Porté-Agel, Fernando, 2015. "Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm," Renewable Energy, Elsevier, vol. 75(C), pages 945-955.
    3. Stevens, Richard J.A.M. & Graham, Jason & Meneveau, Charles, 2014. "A concurrent precursor inflow method for Large Eddy Simulations and applications to finite length wind farms," Renewable Energy, Elsevier, vol. 68(C), pages 46-50.
    4. Fernando Porté-Agel & Yu-Ting Wu & Chang-Hung Chen, 2013. "A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm," Energies, MDPI, vol. 6(10), pages 1-17, October.
    5. Leonardo P. Chamorro & Fernando Porté-Agel, 2011. "Turbulent Flow Inside and Above a Wind Farm: A Wind-Tunnel Study," Energies, MDPI, vol. 4(11), pages 1-21, November.
    6. 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.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    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. Deskos, Georgios & Laizet, Sylvain & Piggott, Matthew D., 2019. "Turbulence-resolving simulations of wind turbine wakes," Renewable Energy, Elsevier, vol. 134(C), pages 989-1002.
    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. 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.
    4. 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).
    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. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    7. 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.
    8. 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.
    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. Gao, Zhiteng & Li, Ye & Wang, Tongguang & Shen, Wenzhong & Zheng, Xiaobo & Pröbsting, Stefan & Li, Deshun & Li, Rennian, 2021. "Modelling the nacelle wake of a horizontal-axis wind turbine under different yaw conditions," Renewable Energy, Elsevier, vol. 172(C), pages 263-275.
    11. Ka Ling Wu & Fernando Porté-Agel, 2017. "Flow Adjustment Inside and Around Large Finite-Size Wind Farms," Energies, MDPI, vol. 10(12), pages 1-23, December.
    12. 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.
    13. 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.
    14. Amin Niayifar & Fernando Porté-Agel, 2016. "Analytical Modeling of Wind Farms: A New Approach for Power Prediction," Energies, MDPI, vol. 9(9), pages 1-13, September.
    15. Tristan Revaz & Fernando Porté-Agel, 2021. "Large-Eddy Simulation of Wind Turbine Flows: A New Evaluation of Actuator Disk Models," Energies, MDPI, vol. 14(13), pages 1-22, June.
    16. Pankaj K. Jha & Earl P. N. Duque & Jessica L. Bashioum & Sven Schmitz, 2015. "Unraveling the Mysteries of Turbulence Transport in a Wind Farm," Energies, MDPI, vol. 8(7), pages 1-29, June.
    17. Wu, Yu-Ting & Liao, Teh-Lu & Chen, Chang-Kuo & Lin, Chuan-Yao & Chen, Po-Wei, 2019. "Power output efficiency in large wind farms with different hub heights and configurations," Renewable Energy, Elsevier, vol. 132(C), pages 941-949.
    18. Huiwen Liu & Imran Hayat & Yaqing Jin & Leonardo P. Chamorro, 2018. "On the Evolution of the Integral Time Scale within Wind Farms," Energies, MDPI, vol. 11(1), pages 1-11, January.
    19. 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.
    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:116:y:2018:i:pa:p:470-478. 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.