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On the Annual Cycle of Meteorological and Geographical Potential of Wind Energy: A Case Study from Southwest Germany

Author

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  • Leonie Grau

    (Environmental Meteorology, University of Freiburg, Werthmannstrasse 10, D-79085 Freiburg, Germany)

  • Christopher Jung

    (Environmental Meteorology, University of Freiburg, Werthmannstrasse 10, D-79085 Freiburg, Germany)

  • Dirk Schindler

    (Environmental Meteorology, University of Freiburg, Werthmannstrasse 10, D-79085 Freiburg, Germany)

Abstract

Wind energy in Germany has experienced high growth rates over the last few years. The set political target in the German federal state of Baden-Wuerttemberg is to raise the share of wind energy in the overall electricity supply to 10% by 2020. To achieve this goal, detailed information on wind energy potential in Baden-Wuerttemberg is necessary. This study assesses the geographical wind energy potential (GP) in Baden-Wuerttemberg giving a guideline to identify suitable locations for wind energy utilization. The focus of this investigation lies in assessing GP for the mean annual meteorological wind energy potential (MP) as well as for the mean MP in December and August providing information on the seasonal behavior of wind power availability. A GIS-based approach is employed to identify sites without geographical restrictions and with sufficient MP at hub heights of 100 m, 140 m, and 200 m. The study finds that (1) the number of possible sites for wind energy utilization is strongly limited by geographical restrictions, (2) GP is highly dependent on MP and, therefore, (3) GP varies highly throughout a year since MP depends on the seasonal pattern of wind speed in Central Europe, showing high values in winter and low values in summer.

Suggested Citation

  • Leonie Grau & Christopher Jung & Dirk Schindler, 2017. "On the Annual Cycle of Meteorological and Geographical Potential of Wind Energy: A Case Study from Southwest Germany," Sustainability, MDPI, vol. 9(7), pages 1-11, July.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1169-:d:103558
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    References listed on IDEAS

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    Cited by:

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    5. Wimhurst, Joshua J. & Greene, J. Scott & Koch, Jennifer, 2023. "Predicting commercial wind farm site suitability in the conterminous United States using a logistic regression model," Applied Energy, Elsevier, vol. 352(C).

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