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UAV Photogrammetry Application for Determining the Influence of Shading on Solar Photovoltaic Array Energy Efficiency

Author

Listed:
  • Vytautas Bocullo

    (Centre for Smart Cities and Infrastructure, Kaunas University of Technology, Studentų g. 48, 51367 Kaunas, Lithuania)

  • Linas Martišauskas

    (Lithuanian Energy Institute, Breslaujos g. 3, 44403 Kaunas, Lithuania)

  • Darius Pupeikis

    (Centre for Smart Cities and Infrastructure, Kaunas University of Technology, Studentų g. 48, 51367 Kaunas, Lithuania)

  • Ramūnas Gatautis

    (Lithuanian Energy Institute, Breslaujos g. 3, 44403 Kaunas, Lithuania)

  • Rytis Venčaitis

    (Centre for Smart Cities and Infrastructure, Kaunas University of Technology, Studentų g. 48, 51367 Kaunas, Lithuania)

  • Rimantas Bakas

    (Lithuanian Energy Institute, Breslaujos g. 3, 44403 Kaunas, Lithuania)

Abstract

The field of solar photovoltaic (PV) plants has seen significant growth in recent years, with an increasing number of installations being developed worldwide. However, despite advancements in technology and design, the impact of shading on the performance of PV plants remains an area of concern. Accurate 3D models produced using unmanned aerial vehicle (UAV) photogrammetry can provide aid to evaluate shading from nearby surroundings and to determine the potential of a site for electricity production via solar PV plants. The main objective of this paper is to address the problem of shadows significantly reducing energy yield in solar PV plants by proposing a methodology that aims at assessing the shading effects on PV systems and determining the optimal configuration for a PV module array using an accurate digital environment 3D model built using UAV photogrammetry. A high-level-of-detail 3D model allows us to evaluate possible obstacles for PV module array construction and accurately recreate the proximities that can cast shadows. The methodology was applied to grid-connected PV systems in Kaunas, Lithuania. The results of the case study show that electricity production in PV modules is highest at a 15° tilt angle when the distance between PV rows is 1.25 m. The proposed methodology gives an 11% difference in PV yield due to shading compared with other tools that do not include shading. This study also highlights that at least 30% financing support is necessary for solar PV plants to be economically attractive, resulting in a payback of 9 years and an internal rate of return of 8%. Additionally, this study can help optimize the design and layout of PV systems, making them more efficient and cost-effective.

Suggested Citation

  • Vytautas Bocullo & Linas Martišauskas & Darius Pupeikis & Ramūnas Gatautis & Rytis Venčaitis & Rimantas Bakas, 2023. "UAV Photogrammetry Application for Determining the Influence of Shading on Solar Photovoltaic Array Energy Efficiency," Energies, MDPI, vol. 16(3), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1292-:d:1046763
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    References listed on IDEAS

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    1. Gallardo-Saavedra, Sara & Hernández-Callejo, Luis & Duque-Perez, Oscar, 2018. "Technological review of the instrumentation used in aerial thermographic inspection of photovoltaic plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 566-579.
    2. Diane Palmer & Elena Koumpli & Ian Cole & Ralph Gottschalg & Thomas Betts, 2018. "A GIS-Based Method for Identification of Wide Area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry," Energies, MDPI, vol. 11(12), pages 1-22, December.
    3. Farhadi, Rouhollah & Taki, Morteza, 2020. "The energy gain reduction due to shadow inside a flat-plate solar collector," Renewable Energy, Elsevier, vol. 147(P1), pages 730-740.
    4. Martín Silva & Justo Jose Roberts & Pedro Osvaldo Prado, 2021. "Calculation of the Shading Factors for Solar Modules with MATLAB," Energies, MDPI, vol. 14(15), pages 1-23, August.
    5. Odysseas Tsafarakis & Kostas Sinapis & Wilfried G. J. H. M. van Sark, 2019. "A Time-Series Data Analysis Methodology for Effective Monitoring of Partially Shaded Photovoltaic Systems," Energies, MDPI, vol. 12(9), pages 1-18, May.
    6. Pawita Bunme & Shuhei Yamamoto & Atsushi Shiota & Yasunori Mitani, 2021. "GIS-Based Distribution System Planning for New PV Installations," Energies, MDPI, vol. 14(13), pages 1-18, June.
    7. Trzmiel, G. & Głuchy, D. & Kurz, D., 2020. "The impact of shading on the exploitation of photovoltaic installations," Renewable Energy, Elsevier, vol. 153(C), pages 480-498.
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