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Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany

Author

Listed:
  • Marcus Eichhorn

    (Department of Bioenergy, Helmholtz Centre for Environmental Research GmbH-UFZ, 04318 Leipzig, Germany)

  • Mattes Scheftelowitz

    (Department of Bioenergy Systems, Deutsches Biomasseforschungszentrum DBFZ, 04347 Leipzig, Germany)

  • Matthias Reichmuth

    (Leipziger Institut für Energie GmbH, Lessingstraße 2, 04109 Leipzig, Germany)

  • Christian Lorenz

    (Leipziger Institut für Energie GmbH, Lessingstraße 2, 04109 Leipzig, Germany)

  • Kyriakos Louca

    (Leipziger Institut für Energie GmbH, Lessingstraße 2, 04109 Leipzig, Germany)

  • Alexander Schiffler

    (Leipziger Institut für Energie GmbH, Lessingstraße 2, 04109 Leipzig, Germany)

  • Rita Keuneke

    (Ingenieurbüro Floecksmühle GmbH, 52066 Aachen, Germany)

  • Martin Bauschmann

    (Department of Bioenergy Systems, Deutsches Biomasseforschungszentrum DBFZ, 04347 Leipzig, Germany)

  • Jens Ponitka

    (Department of Nature Conservation and Renewable Energy, German Federal Agency for Nature Conservation, 04277 Leipzig, Germany)

  • David Manske

    (Department of Bioenergy, Helmholtz Centre for Environmental Research GmbH-UFZ, 04318 Leipzig, Germany
    Department of Bioenergy Systems, Deutsches Biomasseforschungszentrum DBFZ, 04347 Leipzig, Germany)

  • Daniela Thrän

    (Department of Bioenergy, Helmholtz Centre for Environmental Research GmbH-UFZ, 04318 Leipzig, Germany
    Department of Bioenergy Systems, Deutsches Biomasseforschungszentrum DBFZ, 04347 Leipzig, Germany)

Abstract

The expansion of renewable energy technologies, accompanied by an increasingly decentralized supply structure, raises many research questions regarding the structure, dimension, and impacts of the electricity supply network. In this context, information on renewable energy plants, particularly their spatial distribution and key parameters—e.g., installed capacity, total size, and required space—are more and more important for public decision makers and different scientific domains, such as energy system analysis and impact assessment. The dataset described in this paper covers the spatial distribution, installed capacity, and commissioning year of wind turbines, photovoltaic field systems, and bio- and river hydro power plants in Germany. Collected from different online sources and authorities, the data have been thoroughly cross-checked, cleaned, and merged to generate validated and complete datasets. The paper concludes with notes on the practical use of the dataset in an environmental impact monitoring framework and other potential research or policy settings.

Suggested Citation

  • Marcus Eichhorn & Mattes Scheftelowitz & Matthias Reichmuth & Christian Lorenz & Kyriakos Louca & Alexander Schiffler & Rita Keuneke & Martin Bauschmann & Jens Ponitka & David Manske & Daniela Thrän, 2019. "Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany," Data, MDPI, vol. 4(1), pages 1-15, February.
    • Handle: RePEc:gam:jdataj:v:4:y:2019:i:1:p:29-:d:204823
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    References listed on IDEAS

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    3. Welson Bassi & Alcantaro Lemes Rodrigues & Ildo Luis Sauer, 2023. "Dataset on SCADA Data of an Urban Small Wind Turbine Operation in São Paulo, Brazil," Data, MDPI, vol. 8(3), pages 1-9, February.
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    5. David Manske & Lukas Grosch & Julius Schmiedt & Nora Mittelstädt & Daniela Thrän, 2022. "Geo-Locations and System Data of Renewable Energy Installations in Germany," Data, MDPI, vol. 7(9), pages 1-15, September.
    6. Romane Bouchard & Djordje Romanic, 2023. "Monte Carlo modeling of tornado hazard to wind turbines in Germany," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(3), pages 3899-3923, April.
    7. Jennifer Kreklow & Björn Tetzlaff & Gerald Kuhnt & Benjamin Burkhard, 2019. "A Rainfall Data Intercomparison Dataset of RADKLIM, RADOLAN, and Rain Gauge Data for Germany," Data, MDPI, vol. 4(3), pages 1-16, August.

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