Potentials of Renewable Energy Sources in Germany and the Influence of Land Use Datasets

Stanley Risch, Rachel Maier, Junsong Du, Noah Pflugradt, Peter Stenzel, Leander Kotzur and Detlef Stolten
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Stanley Risch: Institute of Energy and Climate Research—Techno-Economic Systems Analysis (IEK-3), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52428 Jülich, Germany
Rachel Maier: Institute of Energy and Climate Research—Techno-Economic Systems Analysis (IEK-3), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52428 Jülich, Germany
Junsong Du: E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Mathieustraße 10, 52074 Aachen, Germany
Noah Pflugradt: Institute of Energy and Climate Research—Techno-Economic Systems Analysis (IEK-3), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52428 Jülich, Germany
Peter Stenzel: Cologne Institute for Renewable Energy (CIRE), Technische Hochschule Köln, Betzdorfer Straße 2, 50679 Cologne, Germany
Leander Kotzur: Institute of Energy and Climate Research—Techno-Economic Systems Analysis (IEK-3), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52428 Jülich, Germany
Detlef Stolten: Institute of Energy and Climate Research—Techno-Economic Systems Analysis (IEK-3), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52428 Jülich, Germany

Energies, 2022, vol. 15, issue 15, 1-25

Abstract: Potential analyses identify possible locations for renewable energy installations, such as wind turbines and photovoltaic arrays. The results of previous potential studies for Germany, however, are not consistent due to different assumptions, methods, and datasets being used. For example, different land-use datasets are applied in the literature to identify suitable areas for technologies requiring open land. For the first time, commonly used datasets are compared regarding the area and position of identified features to analyze their impact on potential analyses. It is shown that the use of Corine Land Cover is not recommended as it leads to potential area overestimation in a typical wind potential analyses by a factor of 4.7 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land-eligibility analyses using the land-use datasets that were proven to be best by our pre-analysis. Moreover, we calculate the rooftop photovoltaic potential using 3D building data nationwide for the first time. The potentials have a high sensitivity towards exclusion conditions, which are also currently discussed in public. For example, if restrictive exclusions are chosen for the onshore wind analysis the necessary potential for climate neutrality cannot be met. The potential capacities and possible locations are published for all administrative levels in Germany in the freely accessible database (Tool for Renewable Energy Potentials—Database), for example, to be incorporated into energy system models.

Keywords: solar-photovoltaics; wind; potential analysis; land-use data; 3D building models; energy system modeling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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