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A comprehensive albedo model for solar energy applications: Geometric spectral albedo

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  • Ziar, Hesan
  • Sönmez, Furkan Fatih
  • Isabella, Olindo
  • Zeman, Miro

Abstract

Albedo is the measure of irradiation energy, which comes from reflecting surroundings. Location, time, geometry, and weather conditions influence the value of albedo. By altering any of the aforementioned parameters, even a little, the albedo value changes. This makes albedo challenging to model. Here we present a mathematical model to cluster all the influential parameters, which affect albedo. We show how complexity of albedo can be expressed as function of reflected spectrum of shadows geometry in a 3-dimensional environment. Performance of the suggested model is examined through real-time measurements and compared with other models. Absolute deviation between modelled and measured average diurnal albedos for a geometrically complex location containing several materials was less than 0.31%. The model also proves that the albedo of a surface is always lower than or equal to its reflectivity. The model can be applied in computer simulation to remotely calculate the value of albedo without the need of in-situ measurements. We show how the proposed model can be used in many fields of research related to climate science, computer graphics, geology, agriculture, solar energy and photovoltaics.

Suggested Citation

  • Ziar, Hesan & Sönmez, Furkan Fatih & Isabella, Olindo & Zeman, Miro, 2019. "A comprehensive albedo model for solar energy applications: Geometric spectral albedo," Applied Energy, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:appene:v:255:y:2019:i:c:s0306261919315545
    DOI: 10.1016/j.apenergy.2019.113867
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    Citations

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    Cited by:

    1. Pouran, Hamid & Padilha Campos Lopes, Mariana & Ziar, Hesan & Alves Castelo Branco, David & Sheng, Yong, 2022. "Evaluating floating photovoltaics (FPVs) potential in providing clean energy and supporting agricultural growth in Vietnam," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    2. Katsikogiannis, Odysseas Alexandros & Ziar, Hesan & Isabella, Olindo, 2022. "Integration of bifacial photovoltaics in agrivoltaic systems: A synergistic design approach," Applied Energy, Elsevier, vol. 309(C).
    3. Lukač, Niko & Špelič, Denis & Štumberger, Gorazd & Žalik, Borut, 2020. "Optimisation for large-scale photovoltaic arrays’ placement based on Light Detection And Ranging data," Applied Energy, Elsevier, vol. 263(C).
    4. Jasiewicz Jarosław & Cierniewski Jerzy, 2021. "SALBEC – A Python Library and GUI Application to Calculate the Diurnal Variation of the Soil Albedo," Quaestiones Geographicae, Sciendo, vol. 40(3), pages 95-107, September.
    5. Eva-Maria Grommes & Ulf Blieske & Jean-Régis Hadji-Minaglou, 2023. "Positive Impact of Red Soil on Albedo and the Annual Yield of Bifacial Photovoltaic Systems in Ghana," Energies, MDPI, vol. 16(4), pages 1-12, February.
    6. Ortega, Eneko & Suarez, Sergio & Jimeno, Juan Carlos & Gutierrez, Jose Rubén & Fano, Vanesa & Otaegi, Aloña & Rivas, Jose Manuel & Navas, Gustavo & Fernandez, Ignacio & Rodriguez-Conde, Sofia, 2024. "An statistical model for the short-term albedo estimation applied to PV bifacial modules," Renewable Energy, Elsevier, vol. 221(C).
    7. Tsvetkov, Nikolay Aleksandrovich & Krivoshein, Ujriy Olegovich & Tolstykh, Aleksandr Vital’yevich & Khutornoi, Andrey Nikolaevich & Boldyryev, Stanislav, 2020. "The calculation of solar energy used by hot water systems in permafrost region: An experimental case study for Yakutia," Energy, Elsevier, vol. 210(C).

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