IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i8p1915-d345265.html
   My bibliography  Save this article

Comparison of Different Driving Modes for the Wind Turbine Wake in Wind Tunnels

Author

Listed:
  • Bingzheng Dou

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

  • Zhanpei Yang

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

  • Michele Guala

    (St. Anthony Falls Laboratory, Department of Civil, Environmental, & Geo-Engineering, University of Minnesota, Minneapolis, MN 55414, USA)

  • Timing Qu

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

  • Liping Lei

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

  • Pan Zeng

    (Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China)

Abstract

The wake of upstream wind turbine is known to affect the operation of downstream turbines and the overall efficiency of the wind farm. Wind tunnel experiments provide relevant information for understanding and modeling the wake and its dependency on the turbine operating conditions. There are always two main driving modes to operate turbines in a wake experiment: (1) the turbine rotor is driven and controlled by a motor, defined active driving mode; (2) the rotor is driven by the incoming wind and subject to a drag torque, defined passive driving mode. The effect of the varying driving mode on the turbine wake is explored in this study. The mean wake velocities, turbulence intensities, skewness and kurtosis of the velocity time-series estimated from hot-wire anemometry data, were obtained at various downstream locations, in a uniform incoming flow wind tunnel and in an atmospheric boundary layer wind tunnel. The results show that there is not a significant difference in the mean wake velocity between these two driving modes. An acceptable agreement is observed in the comparison of wake turbulence intensity and higher-order statistics in the two wind tunnels.

Suggested Citation

  • Bingzheng Dou & Zhanpei Yang & Michele Guala & Timing Qu & Liping Lei & Pan Zeng, 2020. "Comparison of Different Driving Modes for the Wind Turbine Wake in Wind Tunnels," Energies, MDPI, vol. 13(8), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:1915-:d:345265
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/8/1915/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/8/1915/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (Part I: Power performance)," Energy, Elsevier, vol. 113(C), pages 713-722.
    2. 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.
    3. Xie, Wei & Zeng, Pan & Lei, Liping, 2017. "Wind tunnel testing and improved blade element momentum method for umbrella-type rotor of horizontal axis wind turbine," Energy, Elsevier, vol. 119(C), pages 334-350.
    4. Lignarolo, L.E.M. & Ragni, D. & Krishnaswami, C. & Chen, Q. & Simão Ferreira, C.J. & van Bussel, G.J.W., 2014. "Experimental analysis of the wake of a horizontal-axis wind-turbine model," Renewable Energy, Elsevier, vol. 70(C), pages 31-46.
    5. Li, Qing'an & Kamada, Yasunari & Maeda, Takao & Murata, Junsuke & Yusuke, Nishida, 2016. "Effect of turbulence on power performance of a Horizontal Axis Wind Turbine in yawed and no-yawed flow conditions," Energy, Elsevier, vol. 109(C), pages 703-711.
    6. Xie, Wei & Zeng, Pan & Lei, Liping, 2015. "Wind tunnel experiments for innovative pitch regulated blade of horizontal axis wind turbine," Energy, Elsevier, vol. 91(C), pages 1070-1080.
    7. 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.
    8. Göçmen, Tuhfe & Laan, Paul van der & Réthoré, Pierre-Elouan & Diaz, Alfredo Peña & Larsen, Gunner Chr. & Ott, Søren, 2016. "Wind turbine wake models developed at the technical university of Denmark: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 752-769.
    9. Wang, Zhenyu & Ozbay, Ahmet & Tian, Wei & Hu, Hui, 2018. "An experimental study on the aerodynamic performances and wake characteristics of an innovative dual-rotor wind turbine," Energy, Elsevier, vol. 147(C), pages 94-109.
    10. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (part II: Wake characteristics)," Energy, Elsevier, vol. 113(C), pages 1304-1315.
    11. Guo, Jia & Zeng, Pan & Lei, Liping, 2019. "Performance of a straight-bladed vertical axis wind turbine with inclined pitch axes by wind tunnel experiments," Energy, Elsevier, vol. 174(C), pages 553-561.
    12. 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.
    13. Ryi, Jaeha & Rhee, Wook & Chang Hwang, Ui & Choi, Jong-Soo, 2015. "Blockage effect correction for a scaled wind turbine rotor by using wind tunnel test data," Renewable Energy, Elsevier, vol. 79(C), pages 227-235.
    14. de Prada Gil, Mikel & Gomis-Bellmunt, Oriol & Sumper, Andreas & Bergas-Jané, Joan, 2012. "Power generation efficiency analysis of offshore wind farms connected to a SLPC (single large power converter) operated with variable frequencies considering wake effects," Energy, Elsevier, vol. 37(1), pages 455-468.
    15. 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. Wang, Xinbao & Cai, Chang & Cai, Shang-Gui & Wang, Tengyuan & Wang, Zekun & Song, Juanjuan & Rong, Xiaomin & Li, Qing'an, 2023. "A review of aerodynamic and wake characteristics of floating offshore wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    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. Zheng, Yidan & Liu, Huiwen & Chamorro, Leonardo P. & Zhao, Zhenzhou & Li, Ye & Zheng, Yuan & Tang, Kexin, 2023. "Impact of turbulence level on intermittent-like events in the wake of a model wind turbine," Renewable Energy, Elsevier, vol. 203(C), pages 45-55.
    4. Meng, Haoran & Su, Hao & Guo, Jia & Qu, Timing & Lei, Liping, 2022. "Experimental investigation on the power and thrust characteristics of a wind turbine model subjected to surge and sway motions," Renewable Energy, Elsevier, vol. 181(C), pages 1325-1337.

    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. 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.
    3. 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).
    4. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Mori, Naoya, 2017. "Investigation of wake characteristics of a Horizontal Axis Wind Turbine in vertical axis direction with field experiments," Energy, Elsevier, vol. 141(C), pages 262-272.
    5. 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).
    6. Li, Qing’an & Maeda, Takao & Kamada, Yasunari & Mori, Naoya, 2017. "Investigation of wake effects on a Horizontal Axis Wind Turbine in field experiments (Part I: Horizontal axis direction)," Energy, Elsevier, vol. 134(C), pages 482-492.
    7. Huanqiang, Zhang & Xiaoxia, Gao & Hongkun, Lu & Qiansheng, Zhao & Xiaoxun, Zhu & Yu, Wang & Fei, Zhao, 2024. "Investigation of a new 3D wake model of offshore floating wind turbines subjected to the coupling effects of wind and wave," Applied Energy, Elsevier, vol. 365(C).
    8. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Hiromori, Yuto, 2018. "Investigation of wake characteristic of a 30 kW rated power Horizontal Axis Wind Turbine with wake model and field measurement," Applied Energy, Elsevier, vol. 225(C), pages 1190-1204.
    9. Li, Qing'an & Wang, Ye & Kamada, Yasunari & Maeda, Takao & Xu, Jianzhong & Zhou, Shuni & Zhang, Fanghong & Cai, Chang, 2022. "Diagonal inflow effect on the wake characteristics of a horizontal axis wind turbine with Gaussian model and field measurements," Energy, Elsevier, vol. 238(PB).
    10. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (part II: Wake characteristics)," Energy, Elsevier, vol. 113(C), pages 1304-1315.
    11. Liang, Xiaoling & Fu, Shifeng & Cai, Fulin & Han, Xingxing & Zhu, Weijun & Yang, Hua & Shen, Wenzhong, 2023. "Experimental investigation on wake characteristics of wind turbine and a new two-dimensional wake model," Renewable Energy, Elsevier, vol. 203(C), pages 373-381.
    12. Kim, Taewan & Kim, Changwook & Song, Jeonghwan & You, Donghyun, 2024. "Optimal control of a wind farm in time-varying wind using deep reinforcement learning," Energy, Elsevier, vol. 303(C).
    13. Haojun Tang & Kit-Ming Lam & Kei-Man Shum & Yongle Li, 2019. "Wake Effect of a Horizontal Axis Wind Turbine on the Performance of a Downstream Turbine," Energies, MDPI, vol. 12(12), pages 1-18, June.
    14. Li, Qing'an & Xu, Jianzhong & Maeda, Takao & Kamada, Yasunari & Nishimura, Shogo & Wu, Guangxing & Cai, Chang, 2019. "Laser Doppler Velocimetry (LDV) measurements of airfoil surface flow on a Horizontal Axis Wind Turbine in boundary layer," Energy, Elsevier, vol. 183(C), pages 341-357.
    15. Meng, Haoran & Ma, Zhe & Dou, Bingzheng & Zeng, Pan & Lei, Liping, 2020. "Investigation on the performance of a novel forward-folding rotor used in a downwind horizontal-axis turbine," Energy, Elsevier, vol. 190(C).
    16. Li, B. & Zhou, D.L. & Wang, Y. & Shuai, Y. & Liu, Q.Z. & Cai, W.H., 2020. "The design of a small lab-scale wind turbine model with high performance similarity to its utility-scale prototype," Renewable Energy, Elsevier, vol. 149(C), pages 435-444.
    17. 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).
    18. 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.
    19. Zhang, Sanxia & Luo, Kun & Yuan, Renyu & Wang, Qiang & Wang, Jianwen & Zhang, Liru & Fan, Jianren, 2018. "Influences of operating parameters on the aerodynamics and aeroacoustics of a horizontal-axis wind turbine," Energy, Elsevier, vol. 160(C), pages 597-611.
    20. Zhu, Xiaoxun & Chen, Yao & Xu, Shinai & Zhang, Shaohai & Gao, Xiaoxia & Sun, Haiying & Wang, Yu & Zhao, Fei & Lv, Tiancheng, 2023. "Three-dimensional non-uniform full wake characteristics for yawed wind turbine with LiDAR-based experimental verification," Energy, Elsevier, vol. 270(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:13:y:2020:i:8:p:1915-:d:345265. 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.