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Thermal models for mono/bifacial modules in ground/floating photovoltaic systems: A review

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  • Osama, Amr
  • Tina, Giuseppe Marco
  • Gagliano, Antonio

Abstract

Since the world's policy tends to rely on solar energy to meet energy needs, photovoltaics are considered a crucial asset that requires continuous monitoring. Several installation solutions, including different PV technologies, created challenges in providing a reliable evaluation to depend on. Thermal modeling is essential to predict the cell temperature that is utilized in anticipating the system's electrical performance, as in most commercial software. Hence, this work provides an overview of the most used thermal models for installation solutions (free-standing, roof-mounted, floating, etc.) utilizing both mono and bifacial module technology. The provided analysis is focused on evaluating the different responses of the thermal models that can be used for the same configuration and technology. A sensitive comparative analysis of the various thermal models is provided to assess their response to the climatic parameters as an input to the thermal model. The analysis revealed that for monofacial thermal models, Ross models underestimate the cell temperature at any radiation intensity, while the Faiman model using PVsyst coefficients generates the highest overestimated cell temperature among the examined models. It can be seen that the effect of wind speed reduces for a velocity higher than 10 m/s. As for the bifacial PV module, it can be noticed that the Sandia model using Bifacial optimized coefficients is very sensitive to the back surface radiation as it tends to overestimate relative to the Faiman model. Furthermore, floating PV thermal models are significantly affected by the heat transfer coefficient that usually produces a lower cell temperature.

Suggested Citation

  • Osama, Amr & Tina, Giuseppe Marco & Gagliano, Antonio, 2025. "Thermal models for mono/bifacial modules in ground/floating photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
  • Handle: RePEc:eee:rensus:v:216:y:2025:i:c:s1364032125003004
    DOI: 10.1016/j.rser.2025.115627
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    1. Cubukcu, M. & Akanalci, A., 2020. "Real-time inspection and determination methods of faults on photovoltaic power systems by thermal imaging in Turkey," Renewable Energy, Elsevier, vol. 147(P1), pages 1231-1238.
    2. Elminshawy, Nabil A.S. & Osama, Amr & Gagliano, Antonio & Oterkus, Erkan & Tina, Giuseppe Marco, 2024. "A technical and economic evaluation of floating photovoltaic systems in the context of the water-energy nexus," Energy, Elsevier, vol. 303(C).
    3. Tina, Giuseppe Marco & Bontempo Scavo, Fausto & Merlo, Leonardo & Bizzarri, Fabrizio, 2021. "Comparative analysis of monofacial and bifacial photovoltaic modules for floating power plants," Applied Energy, Elsevier, vol. 281(C).
    4. Nuria Martín-Chivelet & Jesús Polo & Carlos Sanz-Saiz & Lucy Tamara Núñez Benítez & Miguel Alonso-Abella & José Cuenca, 2022. "Assessment of PV Module Temperature Models for Building-Integrated Photovoltaics (BIPV)," Sustainability, MDPI, vol. 14(3), pages 1-15, January.
    5. Adam Idzkowski & Karolina Karasowska & Wojciech Walendziuk, 2020. "Temperature Analysis of the Stand-Alone and Building Integrated Photovoltaic Systems Based on Simulation and Measurement Data," Energies, MDPI, vol. 13(16), pages 1-23, August.
    6. Muehleisen, W. & Loeschnig, J. & Feichtner, M. & Burgers, A.R. & Bende, E.E. & Zamini, S. & Yerasimou, Y. & Kosel, J. & Hirschl, C. & Georghiou, G.E., 2021. "Energy yield measurement of an elevated PV system on a white flat roof and a performance comparison of monofacial and bifacial modules," Renewable Energy, Elsevier, vol. 170(C), pages 613-619.
    7. Guerrero-Lemus, R. & Cañadillas-Ramallo, D. & Reindl, T. & Valle-Feijóo, J.M., 2019. "A simple big data methodology and analysis of the specific yield of all PV power plants in a power system over a long time period," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 123-132.
    8. Waithiru Charles Lawrence Kamuyu & Jong Rok Lim & Chang Sub Won & Hyung Keun Ahn, 2018. "Prediction Model of Photovoltaic Module Temperature for Power Performance of Floating PVs," Energies, MDPI, vol. 11(2), pages 1-13, February.
    9. Triki-Lahiani, Asma & Bennani-Ben Abdelghani, Afef & Slama-Belkhodja, Ilhem, 2018. "Fault detection and monitoring systems for photovoltaic installations: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2680-2692.
    10. Skoplaki, E. & Palyvos, J.A., 2009. "Operating temperature of photovoltaic modules: A survey of pertinent correlations," Renewable Energy, Elsevier, vol. 34(1), pages 23-29.
    11. Serrano-Luján, L. & Toledo, C. & Colmenar, J.M. & Abad, J. & Urbina, A., 2022. "Accurate thermal prediction model for building-integrated photovoltaics systems using guided artificial intelligence algorithms," Applied Energy, Elsevier, vol. 315(C).
    12. Salim Bouchakour & Daniel Valencia-Caballero & Alvaro Luna & Eduardo Roman & El Amin Kouadri Boudjelthia & Pedro Rodríguez, 2021. "Modelling and Simulation of Bifacial PV Production Using Monofacial Electrical Models," Energies, MDPI, vol. 14(14), pages 1-16, July.
    13. Osma-Pinto, German & Ordóñez-Plata, Gabriel, 2020. "Dynamic thermal modelling for the prediction of the operating temperature of a PV panel with an integrated cooling system," Renewable Energy, Elsevier, vol. 152(C), pages 1041-1054.
    14. Chenni, R. & Makhlouf, M. & Kerbache, T. & Bouzid, A., 2007. "A detailed modeling method for photovoltaic cells," Energy, Elsevier, vol. 32(9), pages 1724-1730.
    15. Gu, Wenbo & Li, Senji & Liu, Xing & Chen, Zhenwu & Zhang, Xiaochun & Ma, Tao, 2021. "Experimental investigation of the bifacial photovoltaic module under real conditions," Renewable Energy, Elsevier, vol. 173(C), pages 1111-1122.
    16. Keddouda, Abdelhak & Ihaddadene, Razika & Boukhari, Ali & Atia, Abdelmalek & Arıcı, Müslüm & Lebbihiat, Nacer & Ihaddadene, Nabila, 2024. "Photovoltaic module temperature prediction using various machine learning algorithms: Performance evaluation," Applied Energy, Elsevier, vol. 363(C).
    17. Atsu, Divine & Seres, Istvan & Aghaei, Mohammadreza & Farkas, Istvan, 2020. "Analysis of long-term performance and reliability of PV modules under tropical climatic conditions in sub-Saharan," Renewable Energy, Elsevier, vol. 162(C), pages 285-295.
    18. Hana Kim & Hun Park, 2018. "PV Waste Management at the Crossroads of Circular Economy and Energy Transition: The Case of South Korea," Sustainability, MDPI, vol. 10(10), pages 1-15, October.
    19. R. Kopecek & J. Libal, 2018. "Towards large-scale deployment of bifacial photovoltaics," Nature Energy, Nature, vol. 3(6), pages 443-446, June.
    20. Abdulla, Hind & Sleptchenko, Andrei & Nayfeh, Ammar, 2024. "Photovoltaic systems operation and maintenance: A review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).
    21. Waqar Akram, M. & Li, Guiqiang & Jin, Yi & Chen, Xiao, 2022. "Failures of Photovoltaic modules and their Detection: A Review," Applied Energy, Elsevier, vol. 313(C).
    22. Mattei, M. & Notton, G. & Cristofari, C. & Muselli, M. & Poggi, P., 2006. "Calculation of the polycrystalline PV module temperature using a simple method of energy balance," Renewable Energy, Elsevier, vol. 31(4), pages 553-567.
    23. Muñoz-Cerón, Emilio & Osorio-Aravena, Juan Carlos & Rodríguez-Segura, Francisco Javier & Frolova, Marina & Ruano-Quesada, Antonio, 2023. "Floating photovoltaics systems on water irrigation ponds: Technical potential and multi-benefits analysis," Energy, Elsevier, vol. 271(C).
    24. Spertino, Filippo & Corona, Fabio, 2013. "Monitoring and checking of performance in photovoltaic plants: A tool for design, installation and maintenance of grid-connected systems," Renewable Energy, Elsevier, vol. 60(C), pages 722-732.
    25. Rouani, Lahcene & Harkat, Mohamed Faouzi & Kouadri, Abdelmalek & Mekhilef, Saad, 2021. "Shading fault detection in a grid-connected PV system using vertices principal component analysis," Renewable Energy, Elsevier, vol. 164(C), pages 1527-1539.
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