IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i8p2899-d794527.html
   My bibliography  Save this article

Large-Eddy Simulation of Wakes of Waked Wind Turbines

Author

Listed:
  • Xiaohao Liu

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhaobin Li

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xiaolei Yang

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Duo Xu

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Seokkoo Kang

    (Civil and Environmental Engineering Department, Hanyang University, Seoul 133791, Korea)

  • Ali Khosronejad

    (Civil Engineering Department, Stony Brook University, Stony Brook, NY 11794, USA)

Abstract

The wake dynamics of a wind turbine are influenced by the atmospheric turbulence and the wake of its upwind turbine. In this work, we investigate the wake characteristics of a waked wind turbine for four different downwind spacings and three different inflows using large-eddy simulation with a turbine parameterized using the actuator surface model. The wake statistics of the waked turbine are compared with those of the stand-alone wind turbine under the same inflow. The results show that the oncoming wake significantly affects the near wake of the waked turbine, where it accelerates the wake recovery by increasing the turbulent convection, and increases the turbulence kinetic energy. The velocity deficit and turbulence kinetic energy in the far wake, on the other hand, are fairly similar with each other for the considered different turbine spacings, and are close to those of the stand-alone wind turbine. As for the wake meandering of the waked wind turbines, it is initiated quickly and enhanced by the oncoming wake turbulence, as shown by the meandering amplitudes and the power spectral density of the instantaneous wake positions. The growth rates of the wake meandering from the waked wind turbines, on the other hand, are close to that of the stand-alone wind turbine, indicating the critical role of the atmospheric turbulence on wake meandering. The present work details how the oncoming wake influences the wake dynamics of the downwind turbine, and provides physical insights on developing engineering models to take into account such effects.

Suggested Citation

  • Xiaohao Liu & Zhaobin Li & Xiaolei Yang & Duo Xu & Seokkoo Kang & Ali Khosronejad, 2022. "Large-Eddy Simulation of Wakes of Waked Wind Turbines," Energies, MDPI, vol. 15(8), pages 1-26, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2899-:d:794527
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/8/2899/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/8/2899/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Xiaolei & Pakula, Maggie & Sotiropoulos, Fotis, 2018. "Large-eddy simulation of a utility-scale wind farm in complex terrain," Applied Energy, Elsevier, vol. 229(C), pages 767-777.
    2. Mycek, Paul & Gaurier, Benoît & Germain, Grégory & Pinon, Grégory & Rivoalen, Elie, 2014. "Experimental study of the turbulence intensity effects on marine current turbines behaviour. Part II: Two interacting turbines," Renewable Energy, Elsevier, vol. 68(C), pages 876-892.
    3. Yang, Xiaolei & Milliren, Christopher & Kistner, Matt & Hogg, Christopher & Marr, Jeff & Shen, Lian & Sotiropoulos, Fotis, 2021. "High-fidelity simulations and field measurements for characterizing wind fields in a utility-scale wind farm," Applied Energy, Elsevier, vol. 281(C).
    4. Chen, Guang & Li, Xiao-Bai & Liang, Xi-Feng, 2022. "IDDES simulation of the performance and wake dynamics of the wind turbines under different turbulent inflow conditions," Energy, Elsevier, vol. 238(PB).
    5. Na, Ji Sung & Koo, Eunmo & Ko, Seung Chul & Linn, Rodman & Muñoz-Esparza, Domingo & Jin, Emilia Kyung & Lee, Joon Sang, 2019. "Stochastic characteristics for the vortical structure of a 5-MW wind turbine wake," Renewable Energy, Elsevier, vol. 133(C), pages 1220-1230.
    6. Gao, Xiaoxia & Wang, Tengyuan & Li, Bingbing & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Zhao, Fei, 2019. "Investigation of wind turbine performance coupling wake and topography effects based on LiDAR measurements and SCADA data," Applied Energy, Elsevier, vol. 255(C).
    7. Xiaolei Yang & Fotis Sotiropoulos, 2019. "A Review on the Meandering of Wind Turbine Wakes," Energies, MDPI, vol. 12(24), pages 1-20, December.
    8. Wu, Chutian & Yang, Xiaolei & Zhu, Yaxin, 2021. "On the design of potential turbine positions for physics-informed optimization of wind farm layout," Renewable Energy, Elsevier, vol. 164(C), pages 1108-1120.
    9. 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.
    10. Yang, Xiaolei & Khosronejad, Ali & Sotiropoulos, Fotis, 2017. "Large-eddy simulation of a hydrokinetic turbine mounted on an erodible bed," Renewable Energy, Elsevier, vol. 113(C), pages 1419-1433.
    11. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Li, Qi, 2019. "A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes," Applied Energy, Elsevier, vol. 233, pages 975-984.
    12. Takanori Uchida, 2020. "Effects of Inflow Shear on Wake Characteristics of Wind-Turbines over Flat Terrain," Energies, MDPI, vol. 13(14), pages 1-31, July.
    13. Li, Li & Huang, Zhi & Ge, Mingwei & Zhang, Qiying, 2022. "A novel three-dimensional analytical model of the added streamwise turbulence intensity for wind-turbine wakes," Energy, Elsevier, vol. 238(PB).
    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. Zhang, Yi & Li, Zhaobin & Liu, Xiaohao & Sotiropoulos, Fotis & Yang, Xiaolei, 2023. "Turbulence in waked wind turbine wakes: Similarity and empirical formulae," Renewable Energy, Elsevier, vol. 209(C), pages 27-41.

    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. 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).
    2. Wang, Tengyuan & Cai, Chang & Wang, Xinbao & Wang, Zekun & Chen, Yewen & Song, Juanjuan & Xu, Jianzhong & Zhang, Yuning & Li, Qingan, 2023. "A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow," Energy, Elsevier, vol. 271(C).
    3. 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).
    4. Wu, Chutian & Yang, Xiaolei & Zhu, Yaxin, 2021. "On the design of potential turbine positions for physics-informed optimization of wind farm layout," Renewable Energy, Elsevier, vol. 164(C), pages 1108-1120.
    5. Xiaolei Yang & Fotis Sotiropoulos, 2019. "A Review on the Meandering of Wind Turbine Wakes," Energies, MDPI, vol. 12(24), pages 1-20, December.
    6. Zhaobin Li & Xiaohao Liu & Xiaolei Yang, 2022. "Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes," Energies, MDPI, vol. 15(18), pages 1-28, September.
    7. Yunliang Li & Zhaobin Li & Zhideng Zhou & Xiaolei Yang, 2023. "Large-Eddy Simulation of Wind Turbine Wakes in Forest Terrain," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    8. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
    9. Fei Zhao & Yihan Gao & Tengyuan Wang & Jinsha Yuan & Xiaoxia Gao, 2020. "Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    10. Clemente Gotelli & Mirko Musa & Michele Guala & Cristián Escauriaza, 2019. "Experimental and Numerical Investigation of Wake Interactions of Marine Hydrokinetic Turbines," Energies, MDPI, vol. 12(16), pages 1-17, August.
    11. Rivera-Arreba, Irene & Li, Zhaobin & Yang, Xiaolei & Bachynski-Polić, Erin E., 2024. "Comparison of the dynamic wake meandering model against large eddy simulation for horizontal and vertical steering of wind turbine wakes," Renewable Energy, Elsevier, vol. 221(C).
    12. Zhang, Jincheng & Zhao, Xiaowei, 2020. "Quantification of parameter uncertainty in wind farm wake modeling," Energy, Elsevier, vol. 196(C).
    13. Zhang, Jincheng & Zhao, Xiaowei, 2020. "A novel dynamic wind farm wake model based on deep learning," Applied Energy, Elsevier, vol. 277(C).
    14. Zhang, Yi & Li, Zhaobin & Liu, Xiaohao & Sotiropoulos, Fotis & Yang, Xiaolei, 2023. "Turbulence in waked wind turbine wakes: Similarity and empirical formulae," Renewable Energy, Elsevier, vol. 209(C), pages 27-41.
    15. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions," Applied Energy, Elsevier, vol. 242(C), pages 1383-1395.
    16. Ju, Xinglong & Liu, Feng, 2019. "Wind farm layout optimization using self-informed genetic algorithm with information guided exploitation," Applied Energy, Elsevier, vol. 248(C), pages 429-445.
    17. Gao, Xiaoxia & Li, Bingbing & Wang, Tengyuan & Sun, Haiying & Yang, Hongxing & Li, Yonghua & Wang, Yu & Zhao, Fei, 2020. "Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements," Applied Energy, Elsevier, vol. 260(C).
    18. Gao, Xiaoxia & Zhang, Shaohai & Li, Luqing & Xu, Shinai & Chen, Yao & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu & Lu, Hao, 2022. "Quantification of 3D spatiotemporal inhomogeneity for wake characteristics with validations from field measurement and wind tunnel test," Energy, Elsevier, vol. 254(PA).
    19. Radünz, William Corrêa & Sakagami, Yoshiaki & Haas, Reinaldo & Petry, Adriane Prisco & Passos, Júlio César & Miqueletti, Mayara & Dias, Eduardo, 2021. "Influence of atmospheric stability on wind farm performance in complex terrain," Applied Energy, Elsevier, vol. 282(PA).
    20. Zhang, Shaohai & Duan, Huanfeng & Lu, Lin & He, Ruiyang & Gao, Xiaoxia & Zhu, Songye, 2024. "Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy," Energy, Elsevier, vol. 294(C).

    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:gam:jeners:v:15:y:2022:i:8:p:2899-:d:794527. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.