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Modelling the building-related photovoltaic power production potential in the light of the EU's Solar Rooftop Initiative

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  • Molnár, Gergely
  • Cabeza, Luisa F.
  • Chatterjee, Souran
  • Ürge-Vorsatz, Diana

Abstract

Decarbonizing the building sector is key to meet the EU climate goals by 2050. Although the recent policies recognized the importance of on-site solar energy production in the energy transition, there are only a few modelling studies analyzing how much the gap between the technically possible and policy-driven power generation of rooftop photovoltaic (PV) panels can be reduced. This study, therefore, uses geospatial techniques and the high-resolution Building Integrated Solar Energy (BISE) supply model to estimate the main spatial and temporal characteristics of the rooftop PV energy production potential. To support decision-making, important implications of the Solar Rooftop Initiative action plan of the European Commission on the future dimension of the PV electricity supply are also assessed in the context of the achievable potential. The modelling results indicate that the current rooftop PV technical potential could be about 2.7 PWh, being in similar extent with the EU power consumption. The largest country-level PV potentials can be found in Germany, France, Italy and Poland, with an increase of 30% by 2060. Our findings also underline that by following the latest policies, major improvement could be achieved in the EU's rooftop solar energy production by around 2040, depending greatly on the structure and energy efficiency niveau of the future building stock.

Suggested Citation

  • Molnár, Gergely & Cabeza, Luisa F. & Chatterjee, Souran & Ürge-Vorsatz, Diana, 2024. "Modelling the building-related photovoltaic power production potential in the light of the EU's Solar Rooftop Initiative," Applied Energy, Elsevier, vol. 360(C).
    • Handle: RePEc:eee:appene:v:360:y:2024:i:c:s0306261924000916
    DOI: 10.1016/j.apenergy.2024.122708
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    1. Siddharth Joshi & Shivika Mittal & Paul Holloway & Priyadarshi Ramprasad Shukla & Brian Ó Gallachóir & James Glynn, 2021. "High resolution global spatiotemporal assessment of rooftop solar photovoltaics potential for renewable electricity generation," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    2. Buffat, René & Grassi, Stefano & Raubal, Martin, 2018. "A scalable method for estimating rooftop solar irradiation potential over large regions," Applied Energy, Elsevier, vol. 216(C), pages 389-401.
    3. Kougias, Ioannis & Taylor, Nigel & Kakoulaki, Georgia & Jäger-Waldau, Arnulf, 2021. "The role of photovoltaics for the European Green Deal and the recovery plan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    4. Zhong, Teng & Zhang, Zhixin & Chen, Min & Zhang, Kai & Zhou, Zixuan & Zhu, Rui & Wang, Yijie & Lü, Guonian & Yan, Jinyue, 2021. "A city-scale estimation of rooftop solar photovoltaic potential based on deep learning," Applied Energy, Elsevier, vol. 298(C).
    5. Gómez-Navarro, Tomás & Brazzini, Tommaso & Alfonso-Solar, David & Vargas-Salgado, Carlos, 2021. "Analysis of the potential for PV rooftop prosumer production: Technical, economic and environmental assessment for the city of Valencia (Spain)," Renewable Energy, Elsevier, vol. 174(C), pages 372-381.
    6. Yang, Ying & Campana, Pietro Elia & Stridh, Bengt & Yan, Jinyue, 2020. "Potential analysis of roof-mounted solar photovoltaics in Sweden," Applied Energy, Elsevier, vol. 279(C).
    7. Walch, Alina & Castello, Roberto & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2020. "Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty," Applied Energy, Elsevier, vol. 262(C).
    8. Rita Remeikienė & Ligita Gasparėnienė & Aleksandra Fedajev & Marek Szarucki & Marija Đekić & Jolita Razumienė, 2021. "Evaluation of Sustainable Energy Development Progress in EU Member States in the Context of Building Renovation," Energies, MDPI, vol. 14(14), pages 1-22, July.
    9. Paulius Kozlovas & Saulius Gudzius & Jokubas Ciurlionis & Audrius Jonaitis & Inga Konstantinaviciute & Viktorija Bobinaite, 2023. "Assessment of Technical and Economic Potential of Urban Rooftop Solar Photovoltaic Systems in Lithuania," Energies, MDPI, vol. 16(14), pages 1-29, July.
    10. Fina, Bernadette & Auer, Hans & Friedl, Werner, 2020. "Cost-optimal economic potential of shared rooftop PV in energy communities: Evidence from Austria," Renewable Energy, Elsevier, vol. 152(C), pages 217-228.
    11. Gernaat, David E.H.J. & de Boer, Harmen-Sytze & Dammeier, Louise C. & van Vuuren, Detlef P., 2020. "The role of residential rooftop photovoltaic in long-term energy and climate scenarios," Applied Energy, Elsevier, vol. 279(C).
    12. Ordóñez, J. & Jadraque, E. & Alegre, J. & Martínez, G., 2010. "Analysis of the photovoltaic solar energy capacity of residential rooftops in Andalusia (Spain)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2122-2130, September.
    13. Andrea Zambito & Giovanni Pernigotto & Simon Pezzutto & Andrea Gasparella, 2022. "Parametric Urban-Scale Analysis of Space Cooling Energy Needs and Potential Photovoltaic Integration in Residential Districts in South-West Europe," Sustainability, MDPI, vol. 14(11), pages 1-19, May.
    14. Jäger-Waldau, Arnulf & Kougias, Ioannis & Taylor, Nigel & Thiel, Christian, 2020. "How photovoltaics can contribute to GHG emission reductions of 55% in the EU by 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    15. Bódis, Katalin & Kougias, Ioannis & Jäger-Waldau, Arnulf & Taylor, Nigel & Szabó, Sándor, 2019. "A high-resolution geospatial assessment of the rooftop solar photovoltaic potential in the European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    16. Sun, Tao & Shan, Ming & Rong, Xing & Yang, Xudong, 2022. "Estimating the spatial distribution of solar photovoltaic power generation potential on different types of rural rooftops using a deep learning network applied to satellite images," Applied Energy, Elsevier, vol. 315(C).
    17. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
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