IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v195y2022icp293-310.html
   My bibliography  Save this article

The space-time structure of turbulence for lidar-assisted wind turbine control

Author

Listed:
  • Guo, Feng
  • Mann, Jakob
  • Peña, Alfredo
  • Schlipf, David
  • Cheng, Po Wen

Abstract

Lidar-assisted wind turbine control has been proven to be beneficial for turbine load reduction. It relies on the preview of incoming turbulence provided by a nacelle lidar, which allows the turbine controller to react to the flow disturbances before their impact on the turbine. When assessing its benefits, previous studies mainly use the standard turbulence parameters suggested by the IEC 61400-1 standard and assume Taylor's frozen hypothesis. Based on atmospheric turbulence observations, the parameters of the Mann spectral turbulence model differ significantly from the values recommended in the standard, and they vary, e.g., with atmospheric stability. Also, turbulence evolution from upstream to the rotor position conflicts with the frozen turbulence hypothesis, and its effect on the preview quality by a nacelle lidar still needs quantification. This work presents a simple method to extend the Mann model to account for the temporal evolution of turbulence using a space-time spectral velocity tensor. Under various atmospheric stability conditions, we derive the space-time tensor parameters and evaluate the space-time tensor using data from a five-beam lidar and a meteorological mast, we found good agreement between the space-time tensor and the measurement data. In addition, a numerical method for simulating a four-dimensional (4D) space-time velocity field based on the space-time tensor is presented. In the end, we analyze the importance of including the temporal evolution of turbulence for assessing lidar wind preview quality.

Suggested Citation

  • Guo, Feng & Mann, Jakob & Peña, Alfredo & Schlipf, David & Cheng, Po Wen, 2022. "The space-time structure of turbulence for lidar-assisted wind turbine control," Renewable Energy, Elsevier, vol. 195(C), pages 293-310.
    • Handle: RePEc:eee:renene:v:195:y:2022:i:c:p:293-310
    DOI: 10.1016/j.renene.2022.05.133
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148122007844
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2022.05.133?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. Dimitrov, Nikolay & Natarajan, Anand & Mann, Jakob, 2017. "Effects of normal and extreme turbulence spectral parameters on wind turbine loads," Renewable Energy, Elsevier, vol. 101(C), pages 1180-1193.
    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. Asadi, Meysam & Pourhossein, Kazem, 2021. "Wind farm site selection considering turbulence intensity," Energy, Elsevier, vol. 236(C).
    2. Shitang Ke & Lu Xu & Tongguang Wang, 2019. "Aerodynamic Performance and Wind-Induced Responses of Large Wind Turbine Systems with Meso-Scale Typhoon Effects," Energies, MDPI, vol. 12(19), pages 1-24, September.
    3. Ren, Guorui & Liu, Jinfu & Wan, Jie & Li, Fei & Guo, Yufeng & Yu, Daren, 2018. "The analysis of turbulence intensity based on wind speed data in onshore wind farms," Renewable Energy, Elsevier, vol. 123(C), pages 756-766.
    4. Dai, S.F. & Liu, H.J. & Chu, Y.J. & Lam, H.F. & Peng, H.Y., 2022. "Impact of corner modification on wind characteristics and wind energy potential over flat roofs of tall buildings," Energy, Elsevier, vol. 241(C).
    5. Evans, S.P. & Bradney, D.R. & Clausen, P.D., 2018. "Assessing the IEC simplified fatigue load equations for small wind turbine blades: How simple is too simple?," Renewable Energy, Elsevier, vol. 127(C), pages 24-31.
    6. Doubrawa, Paula & Churchfield, Matthew J. & Godvik, Marte & Sirnivas, Senu, 2019. "Load response of a floating wind turbine to turbulent atmospheric flow," Applied Energy, Elsevier, vol. 242(C), pages 1588-1599.

    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:195:y:2022:i:c:p:293-310. 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.