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Climatological analysis of solar and wind energy in Germany using the Grosswetterlagen classification

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  • Drücke, Jaqueline
  • Borsche, Michael
  • James, Paul
  • Kaspar, Frank
  • Pfeifroth, Uwe
  • Ahrens, Bodo
  • Trentmann, Jörg

Abstract

Solar and wind energy play an important role in current and future energy supply in Germany and Europe. The production of renewable energy highly depends on weather conditions resulting in an increasing impact of meteorological fluctuations on energy production. Here, climatological data of solar radiation and wind speed are used to simulate hourly capacity factors for solar and wind energy for Germany from 1995 to 2015. Using renewable energy production data for 2015 these data are converted into time series of generated electrical power. Events with very low energy production, i.e., shortfall events, have been identified and related to large-scale weather regimes over Europe.

Suggested Citation

  • Drücke, Jaqueline & Borsche, Michael & James, Paul & Kaspar, Frank & Pfeifroth, Uwe & Ahrens, Bodo & Trentmann, Jörg, 2021. "Climatological analysis of solar and wind energy in Germany using the Grosswetterlagen classification," Renewable Energy, Elsevier, vol. 164(C), pages 1254-1266.
    • Handle: RePEc:eee:renene:v:164:y:2021:i:c:p:1254-1266
    DOI: 10.1016/j.renene.2020.10.102
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    4. António Couto & Paula Costa & Teresa Simões, 2021. "Identification of Extreme Wind Events Using a Weather Type Classification," Energies, MDPI, vol. 14(13), pages 1-16, July.
    5. Muhammad Amin & Hamad Hussain Shah & Bilal Bashir & Muhammad Azhar Iqbal & Umer Hameed Shah & Muhammad Umair Ali, 2023. "Environmental Assessment of Hydrogen Utilization in Various Applications and Alternative Renewable Sources for Hydrogen Production: A Review," Energies, MDPI, vol. 16(11), pages 1-25, May.
    6. Kies, Alexander & Schyska, Bruno U. & Bilousova, Mariia & El Sayed, Omar & Jurasz, Jakub & Stoecker, Horst, 2021. "Critical review of renewable generation datasets and their implications for European power system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    7. Xiaotian Xia & Liye Xiao, 2023. "Probabilistic Power Flow Method for Hybrid AC/DC Grids Considering Correlation among Uncertainty Variables," Energies, MDPI, vol. 16(6), pages 1-19, March.

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