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Combining the VAS 3D interpolation method and Wind Atlas methodology to produce a high-resolution wind resource map for the Czech Republic

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  • Hanslian, David
  • Hošek, Jiří

Abstract

This paper describes a method that was applied as a part of the creation of a wind map for the Czech Republic. The method (abbreviated VAS/WindAtlas) combines an interpolation method (VAS) with the Wind Atlas methodology applied by using the microscale model WAsP. While WAsP eliminates the site-specific effects around measurement sites to provide generalised wind conditions (GWC), VAS interpolates the GWC over the entire domain and takes into account the general increase of wind speed with altitude. As a result, an altitude-dependent generalised wind map is provided. Then, a final high-resolution calculation is performed by WAsP. The VAS/WindAtlas method is considerably more simplified and less computationally demanding than approaches employing more complex numerical models, but it requires a sufficiently dense network of wind measurements, a thorough data quality evaluation and careful corrections that compensate for the known limitations of the applied data and methods. A comparison of the original wind map with new independent wind measurements, which were obtained after the wind map calculation, was performed with a detailed analysis of the expected errors and uncertainties at the validation sites. The presented VAS/WindAtlas method proved to be good solution to estimate wind resources of Czech Republic.

Suggested Citation

  • Hanslian, David & Hošek, Jiří, 2015. "Combining the VAS 3D interpolation method and Wind Atlas methodology to produce a high-resolution wind resource map for the Czech Republic," Renewable Energy, Elsevier, vol. 77(C), pages 291-299.
    • Handle: RePEc:eee:renene:v:77:y:2015:i:c:p:291-299
    DOI: 10.1016/j.renene.2014.12.013
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    Cited by:

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    3. Samuel Van Ackere & Greet Van Eetvelde & David Schillebeeckx & Enrica Papa & Karel Van Wyngene & Lieven Vandevelde, 2015. "Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods," Energies, MDPI, vol. 8(8), pages 1-22, August.
    4. Tang, Xiao-Yu & Zhao, Shumian & Fan, Bo & Peinke, Joachim & Stoevesandt, Bernhard, 2019. "Micro-scale wind resource assessment in complex terrain based on CFD coupled measurement from multiple masts," Applied Energy, Elsevier, vol. 238(C), pages 806-815.
    5. 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.

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