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A surface-layer wind speed correction: A case-study of Darling station

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  • Olaofe, Zaccheus O.

Abstract

In previous study, the vertical wind speed extrapolation from measurement station to modern turbine hubs over an open homogenous terrain was considered. It was presented that an assumption of wind shear exponent under different stability conditions was an inaccurate representation of the actual wind climates as the precise knowledge of the site's wind characteristics at different levels and seasons are essential for planning and implementation of a proposed energy project. In this study, the surface-layer wind speed correction at Darling using the WRF modeling with mesoscale terrain corrections is presented. An hourly mesoscale modeled winds at 3 km grid spacing obtained for one month are postprocessed for estimation of local wind speed profiles at 10 and 50 m height AGL. The sensitivity of the modeled winds to surface terrain corrections is investigated using mesoscale topography parameterizations. Furthermore, 6-hourly mesoscale modeled and satellite observed winds as well as measurements from Darling station are utilized for validation of the statistical downscaling method utilized for the postprocessing of the boundary layer winds over land. It is presented that the precision of the mesoscale modeled winds for local wind speed estimates at potential site without historical measurements can be significantly improved. The confidence in the validity of this methodology for local wind speed correction is estimated at 96–98%.

Suggested Citation

  • Olaofe, Zaccheus O., 2016. "A surface-layer wind speed correction: A case-study of Darling station," Renewable Energy, Elsevier, vol. 93(C), pages 228-244.
    • Handle: RePEc:eee:renene:v:93:y:2016:i:c:p:228-244
    DOI: 10.1016/j.renene.2016.02.055
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    Cited by:

    1. Tuchtenhagen, Patrícia & Carvalho, Gilvani Gomes de & Martins, Guilherme & Silva, Pollyanne Evangelista da & Oliveira, Cristiano Prestrelo de & de Melo Barbosa Andrade, Lara & Araújo, João Medeiros de, 2020. "WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil," Energy, Elsevier, vol. 190(C).
    2. Yu, Shuang & Vautard, Robert, 2022. "A transfer method to estimate hub-height wind speed from 10 meters wind speed based on machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).

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