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Extending the diabatic surface layer wind shear profile for offshore wind energy

Author

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  • Holtslag, M.C.
  • Bierbooms, W.A.A.M.
  • van Bussel, G.J.W.

Abstract

In this research the diabatic surface layer wind shear model is extended for offshore wind energy purposes to higher altitudes based on Gryning's wind profile and the resistance functions proposed by Byun. The wind profile is in theory applicable up to the boundary layer height, which is parametrized with the Rossby-Montgommery equation. The coefficient c of the Rossby-Montgommery equation is found to be stability dependent with decreasing values up to 0.04 for stable conditions and increasing values up to 0.17 for unstable conditions. The proposed shear profile has been validated with 1 year of offshore observation data, and a significant improvement in accuracy is found compared to traditional surface layer shear profiles or power laws. The influence of adopting this extended shear profile for wind energy is analysed in terms of the kinetic energy flux and blade root fatigue loads experienced by a wind turbine. It is found that, especially for stable conditions, results deviate significantly compared to using the traditional surface layer shear profile. The kinetic energy flux decreases by up to 15%.

Suggested Citation

  • Holtslag, M.C. & Bierbooms, W.A.A.M. & van Bussel, G.J.W., 2017. "Extending the diabatic surface layer wind shear profile for offshore wind energy," Renewable Energy, Elsevier, vol. 101(C), pages 96-110.
    • Handle: RePEc:eee:renene:v:101:y:2017:i:c:p:96-110
    DOI: 10.1016/j.renene.2016.08.031
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    Cited by:

    1. Pérez Albornoz, C. & Escalante Soberanis, M.A. & Ramírez Rivera, V. & Rivero, M., 2022. "Review of atmospheric stability estimations for wind power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    2. Liu, Yongqian & Qiao, Yanhui & Han, Shuang & Tao, Tao & Yan, Jie & Li, Li & Bekhbat, Galsan & Munkhtuya, Erdenebat, 2021. "Rotor equivalent wind speed calculation method based on equivalent power considering wind shear and tower shadow," Renewable Energy, Elsevier, vol. 172(C), pages 882-896.
    3. Fang, Guochang & Tian, Lixin & Fu, Min & Sun, Mei & Du, Ruijin & Lu, Longxi & He, Yu, 2017. "The effect of energy construction adjustment on the dynamical evolution of energy-saving and emission-reduction system in China," Applied Energy, Elsevier, vol. 196(C), pages 180-189.
    4. 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.
    5. Bahamonde, Manuel Ignacio & Litrán, Salvador P., 2019. "Study of the energy production of a wind turbine in the open sea considering the continuous variations of the atmospheric stability and the sea surface roughness," Renewable Energy, Elsevier, vol. 135(C), pages 163-175.
    6. Ju-Young Shin & Changsam Jeong & Jun-Haeng Heo, 2018. "A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property," Energies, MDPI, vol. 11(3), pages 1-27, March.
    7. Abramic, A. & García Mendoza, A. & Haroun, R., 2021. "Introducing offshore wind energy in the sea space: Canary Islands case study developed under Maritime Spatial Planning principles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).

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