IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v133y2019icp1220-1230.html
   My bibliography  Save this article

Stochastic characteristics for the vortical structure of a 5-MW wind turbine wake

Author

Listed:
  • Na, Ji Sung
  • Koo, Eunmo
  • Ko, Seung Chul
  • Linn, Rodman
  • Muñoz-Esparza, Domingo
  • Jin, Emilia Kyung
  • Lee, Joon Sang

Abstract

In this study, we analyze the near-wake characteristics of a 5-MW single wind turbine using a large-eddy simulation with the actuator line method. It is observed that stable helical structures of wake had breaking process due to flow instability with high-frequency turbulence in the analysis of turbulence energy spectra and auto-covariance. For vortical structure detection, the swirling strength criterion showed good performance when describing the tip vortices and their various streaklines. In the stable region, the stable helical structure of the tip vortices was observed with little wake recovery and flow instability. However, in the unstable region, the tip vortices had various streakline advection patterns such as horizontal, upward, and downward. In the statistical analysis of the flow acceleration, the distribution and magnitude of the acceleration in the stable and unstable regions were compared in terms of the probability density function, root mean square, and kurtosis. At the hub height and at the opposite blade tips in the stable region, the kurtosis of the acceleration was approximately 20 and 40, respectively. At the height wherein the wake recovery was dominant in the unstable region, the value of the kurtosis was 67.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:133:y:2019:i:c:p:1220-1230
    DOI: 10.1016/j.renene.2018.08.088
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148118310383
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2018.08.088?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. A. La Porta & Greg A. Voth & Alice M. Crawford & Jim Alexander & Eberhard Bodenschatz, 2001. "Fluid particle accelerations in fully developed turbulence," Nature, Nature, vol. 409(6823), pages 1017-1019, February.
    2. Son, Eunkuk & Lee, Seungmin & Hwang, Byeongho & Lee, Soogab, 2014. "Characteristics of turbine spacing in a wind farm using an optimal design process," Renewable Energy, Elsevier, vol. 65(C), pages 245-249.
    3. Na, Ji Sung & Koo, Eunmo & Muñoz-Esparza, Domingo & Jin, Emilia Kyung & Linn, Rodman & Lee, Joon Sang, 2016. "Turbulent kinetics of a large wind farm and their impact in the neutral boundary layer," Energy, Elsevier, vol. 95(C), pages 79-90.
    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. 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.
    2. 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.

    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. Cuevas-Figueroa, Gabriel & Stansby, Peter K. & Stallard, Timothy, 2022. "Accuracy of WRF for prediction of operational wind farm data and assessment of influence of upwind farms on power production," Energy, Elsevier, vol. 254(PB).
    2. Antonio Colmenar-Santos & Severo Campíez-Romero & Lorenzo Alfredo Enríquez-Garcia & Clara Pérez-Molina, 2014. "Simplified Analysis of the Electric Power Losses for On-Shore Wind Farms Considering Weibull Distribution Parameters," Energies, MDPI, vol. 7(11), pages 1-30, October.
    3. Rafael V. Rodrigues & Corinne Lengsfeld, 2019. "Development of a Computational System to Improve Wind Farm Layout, Part I: Model Validation and Near Wake Analysis," Energies, MDPI, vol. 12(5), pages 1-24, March.
    4. van Dijk, Mike T. & van Wingerden, Jan-Willem & Ashuri, Turaj & Li, Yaoyu, 2017. "Wind farm multi-objective wake redirection for optimizing power production and loads," Energy, Elsevier, vol. 121(C), pages 561-569.
    5. Wang, Qiang & Luo, Kun & Wu, Chunlei & Zhu, Zhaofan & Fan, Jianren, 2022. "Mesoscale simulations of a real onshore wind power base in complex terrain: Wind farm wake behavior and power production," Energy, Elsevier, vol. 241(C).
    6. Carvalho, Jonas C. & Rizza, Umberto & Lovato, Rodrigo & Degrazia, Gervásio A. & Filho, Edson P.M. & Campos, Cláudia R.J., 2009. "Estimation of the Kolmogorov constant by large-eddy simulation in the stable PBL," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1500-1508.
    7. Simone Ferrari & Riccardo Rossi & Annalisa Di Bernardino, 2022. "A Review of Laboratory and Numerical Techniques to Simulate Turbulent Flows," Energies, MDPI, vol. 15(20), pages 1-56, October.
    8. Chen, W., 2006. "Time–space fabric underlying anomalous diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 28(4), pages 923-929.
    9. Sun, Jili & Chen, Zheng & Yu, Hao & Gao, Shan & Wang, Bin & Ying, You & Sun, Yong & Qian, Peng & Zhang, Dahai & Si, Yulin, 2022. "Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines," Renewable Energy, Elsevier, vol. 199(C), pages 71-86.
    10. Sun, HongGuang & Hao, Xiaoxiao & Zhang, Yong & Baleanu, Dumitru, 2017. "Relaxation and diffusion models with non-singular kernels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 590-596.
    11. Wang, Qiang & Luo, Kun & Yuan, Renyu & Zhang, Sanxia & Fan, Jianren, 2019. "Wake and performance interference between adjacent wind farms: Case study of Xinjiang in China by means of mesoscale simulations," Energy, Elsevier, vol. 166(C), pages 1168-1180.
    12. Alain Hertz & Odile Marcotte & Asma Mdimagh & Michel Carreau & François Welt, 2017. "Design of a wind farm collection network when several cable types are available," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(1), pages 62-73, January.
    13. Buen Zhang & Shyuan Cheng & Fanghan Lu & Yuan Zheng & Leonardo P. Chamorro, 2020. "Impact of Topographic Steps in the Wake and Power of a Wind Turbine: Part A—Statistics," Energies, MDPI, vol. 13(23), pages 1-14, December.
    14. Ahmadi-Baloutaki, Mojtaba & Carriveau, Rupp & Ting, David S-K., 2016. "A wind tunnel study on the aerodynamic interaction of vertical axis wind turbines in array configurations," Renewable Energy, Elsevier, vol. 96(PA), pages 904-913.
    15. Zhe Ma & Liping Lei & Earl Dowell & Pan Zeng, 2020. "An Experimental Study on the Actuator Line Method with Anisotropic Regularization Kernel," Energies, MDPI, vol. 13(4), pages 1-19, February.
    16. Huang, Diangui, 2019. "A new turbulence analysis method based on the mean speed and mean free path theory of the molecule thermal motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 66-74.

    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:133:y:2019:i:c:p:1220-1230. 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.