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Surface turbulence intensity as a predictor of extrapolated wind resource to the turbine hub height

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  • Gualtieri, Giovanni

Abstract

Based on power law (PL), a novel method is proposed to extrapolate surface wind speed to the wind turbine (WT) hub height, via assessment of wind shear coefficient (WSC), by only using surface turbulence intensity, a parameter actually regarded as a merely critical one in wind energy studies. A 2-year (2012–2013) dataset from the meteorological mast of Cabauw (Netherlands) was used, including 10-min records collected at 10, 20, 40, and 80 m. WT hub heights of 40 and 80 m have been targeted for the extrapolation, being accomplished based on turbulence intensity observations at 10 and 20 m. Trained over the year 2012, the method was validated over the year 2013.

Suggested Citation

  • Gualtieri, Giovanni, 2015. "Surface turbulence intensity as a predictor of extrapolated wind resource to the turbine hub height," Renewable Energy, Elsevier, vol. 78(C), pages 68-81.
    • Handle: RePEc:eee:renene:v:78:y:2015:i:c:p:68-81
    DOI: 10.1016/j.renene.2015.01.011
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    References listed on IDEAS

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    Cited by:

    1. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
    2. Gualtieri, Giovanni, 2018. "Surface turbulence intensity as a predictor of extrapolated wind resource to the turbine hub height: method's test at a mountain site," Renewable Energy, Elsevier, vol. 120(C), pages 457-467.
    3. Gualtieri, Giovanni, 2016. "Atmospheric stability varying wind shear coefficients to improve wind resource extrapolation: A temporal analysis," Renewable Energy, Elsevier, vol. 87(P1), pages 376-390.
    4. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    5. Gualtieri, Giovanni, 2019. "A comprehensive review on wind resource extrapolation models applied in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 215-233.

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