IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i20p5358-d1769023.html
   My bibliography  Save this article

UAV and 3D Modeling for Automated Rooftop Parameter Analysis and Photovoltaic Performance Estimation

Author

Listed:
  • Wioleta Błaszczak-Bąk

    (Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego St. 2, 10-719 Olsztyn, Poland)

  • Marcin Pacześniak

    (Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego St. 2, 10-719 Olsztyn, Poland)

  • Artur Oleksiak

    (Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego St. 2, 10-719 Olsztyn, Poland)

  • Grzegorz Grunwald

    (Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego St. 2, 10-719 Olsztyn, Poland)

Abstract

The global shift towards renewable energy sources necessitates efficient methods for assessing solar potential in urban areas. Rooftop photovoltaic (PV) systems present a sustainable solution for decentralized energy production; however, their effectiveness is influenced by structural and environmental factors, including roof slope, azimuth, and shading. This study aims to develop and validate a UAV-based methodology for assessing rooftop solar potential in urban areas. The authors propose a low-cost, innovative tool that utilizes a commercial unmanned aerial vehicle (UAV), specifically the DJI Air 3, combined with advanced photogrammetry and 3D modeling techniques to analyze rooftop characteristics relevant to PV installations. The methodology includes UAV-based data collection, image processing to generate high-resolution 3D models, calibration and validation against reference objects, and the estimation of solar potential based on rooftop characteristics and solar irradiance data using the proposed Model Analysis Tool (MAT). MAT is a novel solution introduced and described for the first time in this study, representing an original computational framework for the geometric and energetic analysis of rooftops. The innovative aspect of this study lies in combining consumer-grade UAVs with automated photogrammetry and the MAT, creating a low-cost yet accurate framework for rooftop solar assessment that reduces reliance on high-end surveying methods. By being presented in this study for the first time, MAT expands the methodological toolkit for solar potential evaluation, offering new opportunities for urban energy research and practice. The comparison of PVGIS and MAT shows that MAT consistently predicts higher daily energy yields, ranging from 9 to 12.5% across three datasets. The outcomes of this study contribute to facilitating the broader adoption of solar energy, thereby supporting sustainable energy transitions and climate neutrality goals in the face of increasing urban energy demands.

Suggested Citation

  • Wioleta Błaszczak-Bąk & Marcin Pacześniak & Artur Oleksiak & Grzegorz Grunwald, 2025. "UAV and 3D Modeling for Automated Rooftop Parameter Analysis and Photovoltaic Performance Estimation," Energies, MDPI, vol. 18(20), pages 1-17, October.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:20:p:5358-:d:1769023
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/20/5358/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/20/5358/
    Download Restriction: no
    ---><---

    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:18:y:2025:i:20:p:5358-:d:1769023. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.