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Turbulence upstream of wind turbines: A large-eddy simulation approach to investigate the use of wind lidars

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  • Cortina, G.
  • Calaf, M.

Abstract

Despite the evolution of wind turbines, the way in which in-situ meteorological information is obtained has not evolved much. Wind vane and cup anemometers, installed at the turbines nacelle, right behind the blades, are still used. This near-blade monitoring does not provide any time to readjust the profile of the wind turbine, and subjects the blades and structure to wind gusts and extreme incoming wind conditions. A solution is to install wind lidar devices on the turbine's nacelle. This technique is currently under development as an alternative to traditional in-situ wind anemometry because it can measure the wind vector at substantial distances upwind. However, most used wind lidar systems are optimized for measuring within a fixed upwind range, but at what upwind distance should they interrogate the atmosphere? This work uses Large Eddy Simulations to create a realistic atmospheric flow to evaluate optimal scanning distances to learn about the incoming turbulence as a function of wind farm configuration and atmospheric stratification. A correlation model, based on a modified truncated normal distribution, has also been developed, which could be implemented within the feed-forward collective pitch control of the turbine, allowing for improved wind turbine readjustments.

Suggested Citation

  • Cortina, G. & Calaf, M., 2017. "Turbulence upstream of wind turbines: A large-eddy simulation approach to investigate the use of wind lidars," Renewable Energy, Elsevier, vol. 105(C), pages 354-365.
    • Handle: RePEc:eee:renene:v:105:y:2017:i:c:p:354-365
    DOI: 10.1016/j.renene.2016.12.069
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    References listed on IDEAS

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    1. Cortina, G. & Sharma, V. & Calaf, M., 2017. "Investigation of the incoming wind vector for improved wind turbine yaw-adjustment under different atmospheric and wind farm conditions," Renewable Energy, Elsevier, vol. 101(C), pages 376-386.
    2. Yu-Ting Wu & Fernando Porté-Agel, 2012. "Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study," Energies, MDPI, vol. 5(12), pages 1-23, December.
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    1. Tang, Shengming & Li, Tiantian & Guo, Yun & Zhu, Rong & Qu, Hongya, 2022. "Correction of various environmental influences on Doppler wind lidar based on multiple linear regression model," Renewable Energy, Elsevier, vol. 184(C), pages 933-947.
    2. Gaurier, Benoît & Ikhennicheu, Maria & Germain, Grégory & Druault, Philippe, 2020. "Experimental study of bathymetry generated turbulence on tidal turbine behaviour," Renewable Energy, Elsevier, vol. 156(C), pages 1158-1170.
    3. Yazhou Wang & Xin Cai & Shifa Lin & Bofeng Xu & Yuan Zhang & Saixian Bian, 2022. "Study of Tower Clearance Safety Protection during Extreme Gust Based on Wind Turbine Monitoring Data," Energies, MDPI, vol. 15(12), pages 1-11, June.
    4. Cortina, G. & Sharma, V. & Torres, R. & Calaf, M., 2020. "Mean kinetic energy distribution in finite-size wind farms: A function of turbines’ arrangement," Renewable Energy, Elsevier, vol. 148(C), pages 585-599.

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