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The added value of high resolution regional reanalyses for wind power applications

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  • Frank, Christopher W.
  • Pospichal, Bernhard
  • Wahl, Sabrina
  • Keller, Jan D.
  • Hense, Andreas
  • Crewell, Susanne

Abstract

Atmospheric reanalyses are the only source of spatial and temporal gridded wind information at wind turbine height providing data over several decades in the past. The application potential of reanalyses in the renewable energy sector depends strongly on the quality of the meteorological quantities. While global reanalyses have a resolution of typically 50 km, new regional reanalyses COSMO-REA6 and COSMO-REA2 have about 6 km and 2 km horizontal grid spacing, respectively. Here, we investigate the added value of the new regional reanalyses for the renewable energy sector, especially their application potential for site assessment. Four well established wind towers in Europe are used as reference for this purpose. We find regional reanalyses performing significantly better or at least similar to global reanalyses. Especially marginal distributions show significant improvements e.g. the most extreme temporal wind changes (ramp rates) at typical hub-heights are underrepresented by global reanalyses between −80 and −43% while COSMO-REA2 represents them with relative errors between −14 and +9%. Considering biases, mean absolute errors, and correlations most significant improvements occur close to ground and in areas with complex terrain. Moreover, vertically extrapolated wind measurements which are commonly used for site assessment show a stronger site dependency in their performance than reanalyses.

Suggested Citation

  • Frank, Christopher W. & Pospichal, Bernhard & Wahl, Sabrina & Keller, Jan D. & Hense, Andreas & Crewell, Susanne, 2020. "The added value of high resolution regional reanalyses for wind power applications," Renewable Energy, Elsevier, vol. 148(C), pages 1094-1109.
    • Handle: RePEc:eee:renene:v:148:y:2020:i:c:p:1094-1109
    DOI: 10.1016/j.renene.2019.09.138
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    1. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    2. Akintayo T. Abolude & Wen Zhou & Akintomide Afolayan Akinsanola, 2020. "Evaluation and Projections of Wind Power Resources over China for the Energy Industry Using CMIP5 Models," Energies, MDPI, vol. 13(10), pages 1-16, May.
    3. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    4. Murcia, Juan Pablo & Koivisto, Matti Juhani & Luzia, Graziela & Olsen, Bjarke T. & Hahmann, Andrea N. & Sørensen, Poul Ejnar & Als, Magnus, 2022. "Validation of European-scale simulated wind speed and wind generation time series," Applied Energy, Elsevier, vol. 305(C).
    5. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

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