IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i15p3766-d1446440.html
   My bibliography  Save this article

A Comparative Analysis of Data Source’s Impact on Renewable Energy Scenario Assessment—The Example of Ground-Mounted Photovoltaics in Germany

Author

Listed:
  • Elham Fakharizadehshirazi

    (Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, Germany)

  • Christine Rösch

    (Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, Germany)

Abstract

The German government aims to convert its energy system to renewable energy by 2045. This requires a comprehensive understanding of land eligibility for renewables, particularly land-intensive ground-mounted photovoltaics (GM-PV). Federal states must set aside at least 2% of their land for renewable energy. This target value was derived using a top-down energy demand approach. Georeferenced land use data can be used to make bottom-up estimates. This study investigates how the choice of data source influences the bottom-up evaluation of land eligibility for GM-PV installations in Germany. This study evaluates the quality of data sources and their applicability for GM-PV scenario assessment by comparing the official data source Basis-DLM as the reference with the open-access data sources OpenStreetMap (OSM), Corine Land Cover (CLC), and Copernicus Emergency Management Service (CEMS). The intersection over union (IoU) and Matthews correlation coefficient (MCC) methods were used to analyse the differences in land use and eligibility due to the quality of the data sources and to compare their accuracy. The study’s results show the crucial role of data source selection in estimating the potential for GM-PV in Germany. The results indicate that open-access data overestimate land eligibility by 4.0% to 4.5% compared to the official Basis-DLM data. Spatial similarities and discrepancies between the OSM, CEMS CLC, and Basis-DLM land uses were identified. The CLC data exhibit higher consistency with Basis-DLM. These findings emphasise the importance of selecting the appropriate data source depending on the purpose and the use of official data sources for accurate and spatially differentiated decision-making and project planning at different scales. Open-access data sources can be applied for initial orientation and large-scale rough assessment as they balance data accuracy and accessibility.

Suggested Citation

  • Elham Fakharizadehshirazi & Christine Rösch, 2024. "A Comparative Analysis of Data Source’s Impact on Renewable Energy Scenario Assessment—The Example of Ground-Mounted Photovoltaics in Germany," Energies, MDPI, vol. 17(15), pages 1-11, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3766-:d:1446440
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/15/3766/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/15/3766/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Masurowski, Frank & Drechsler, Martin & Frank, Karin, 2016. "A spatially explicit assessment of the wind energy potential in response to an increased distance between wind turbines and settlements in Germany," Energy Policy, Elsevier, vol. 97(C), pages 343-350.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lehmann, Paul & Tafarte, Philip, 2024. "Exclusion zones for renewable energy deployment: One man’s blessing, another man’s curse," Resource and Energy Economics, Elsevier, vol. 76(C).
    2. Kiunke, Theresa & Gemignani, Natalia & Malheiro, Pedro & Brudermann, Thomas, 2022. "Key factors influencing onshore wind energy development: A case study from the German North Sea region," Energy Policy, Elsevier, vol. 165(C).
    3. Oehlmann, Malte & Glenk, Klaus & Lloyd-Smith, Patrick & Meyerhoff, Jürgen, 2021. "Quantifying landscape externalities of renewable energy development: Implications of attribute cut-offs in choice experiments," Resource and Energy Economics, Elsevier, vol. 65(C).
    4. Sliz-Szkliniarz, B. & Eberbach, J. & Hoffmann, B. & Fortin, M., 2019. "Assessing the cost of onshore wind development scenarios: Modelling of spatial and temporal distribution of wind power for the case of Poland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 514-531.
    5. Thomas Lauf & Kristina Ek & Erik Gawel & Paul Lehmann & Patrik Söderholm, 2020. "The regional heterogeneity of wind power deployment: an empirical investigation of land-use policies in Germany and Sweden," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 63(4), pages 751-778, March.
    6. Jan Stede & Nils May, 2020. "Way Off: The Effect of Minimum Distance Regulation on the Deployment of Wind Power," Discussion Papers of DIW Berlin 1867, DIW Berlin, German Institute for Economic Research.
    7. Peri, Erez & Tal, Alon, 2021. "Is setback distance the best criteria for siting wind turbines under crowded conditions? An empirical analysis," Energy Policy, Elsevier, vol. 155(C).
    8. Unnewehr, Jan Frederick & Jalbout, Eddy & Jung, Christopher & Schindler, Dirk & Weidlich, Anke, 2021. "Getting more with less? Why repowering onshore wind farms does not always lead to more wind power generation – A German case study," Renewable Energy, Elsevier, vol. 180(C), pages 245-257.
    9. Felix Reutter & Martin Drechsler & Erik Gawel & Paul Lehmann, 2024. "Social Costs of Setback Distances for Onshore Wind Turbines: A Model Analysis Applied to the German State of Saxony," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(2), pages 437-463, February.
    10. Jan-Niklas Meier & Paul Lehmann & Bernd Süssmuth & Stephan Wedekind, 2024. "Wind power deployment and the impact of spatial planning policies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(2), pages 491-550, February.
    11. Engelhorn, Thorsten & Müsgens, Felix, 2021. "Why is Germany’s energy transition so expensive? Quantifying the costs of wind-energy decentralisation," Resource and Energy Economics, Elsevier, vol. 65(C).
    12. Lehmann, Paul & Reutter, Felix & Tafarte, Philip, 2023. "Optimal siting of onshore wind turbines: Local disamenities matter," Resource and Energy Economics, Elsevier, vol. 74(C).
    13. Kendziorski, Mario & Göke, Leonard & von Hirschhausen, Christian & Kemfert, Claudia & Zozmann, Elmar, 2022. "Centralized and decentral approaches to succeed the 100% energiewende in Germany in the European context – A model-based analysis of generation, network, and storage investments," Energy Policy, Elsevier, vol. 167(C).
    14. Liebe, Ulf & Bartczak, Anna & Meyerhoff, Jürgen, 2017. "A turbine is not only a turbine: The role of social context and fairness characteristics for the local acceptance of wind power," Energy Policy, Elsevier, vol. 107(C), pages 300-308.
    15. Tobias Rösch & Peter Treffinger & Barbara Koch, 2021. "Regional Flexibility Markets—Solutions to the European Energy Distribution Grid—A Systematic Review and Research Agenda," Energies, MDPI, vol. 14(9), pages 1-32, April.
    16. Eichhorn, Marcus & Masurowski, Frank & Becker, Raik & Thrän, Daniela, 2019. "Wind energy expansion scenarios – A spatial sustainability assessment," Energy, Elsevier, vol. 180(C), pages 367-375.
    17. Jan Stede & Marc Blauert & Nils May, 2021. "Way Off: The Effect of Minimum Distance Regulation on the Deployment and Cost of Wind Power," Discussion Papers of DIW Berlin 1989, DIW Berlin, German Institute for Economic Research.
    18. Lehmann, Paul & Tafarte, Philip, 2023. "The opportunity costs of environmental exclusion zones for renewable energy deployment," UFZ Discussion Papers 2/2023, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
    19. Karakislak, Irmak & Schneider, Nina, 2023. "The mayor said so? The impact of local political figures and social norms on local responses to wind energy projects," Energy Policy, Elsevier, vol. 176(C).
    20. Jiang, Haiyan & Wang, Jianzhou & Wu, Jie & Geng, Wei, 2017. "Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1199-1217.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3766-:d:1446440. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.