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Impact of Non-Uniform Irradiance and Temperature Distribution on the Performance of Photovoltaic Generators

Author

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  • Petrakis Thomas

    (General Department, National and Kapodistrian University of Athens, Evripos Campus, 34400 Psachna, Greece)

  • Aphrodite Ktena

    (General Department, National and Kapodistrian University of Athens, Evripos Campus, 34400 Psachna, Greece)

  • Panagiotis Kosmopoulos

    (Institute for Environmental Research and Sustainable Development of the National Observatory of Athens, 15236 Athens, Greece)

  • John Konstantaras

    (Renewable Energy Sources Laboratory, General Department of the National and Kapodistrian University of Athens, 34400 Psachna, Greece)

  • Michael Vrachopoulos

    (Renewable Energy Sources Laboratory, General Department of the National and Kapodistrian University of Athens, 34400 Psachna, Greece)

Abstract

The use of photovoltaic (PV) panels has increased rapidly in the last few years and as a result has become one of the main sources of renewable energy. In this context, it is important to understand in detail how a PV panel reacts to different environmental conditions and how these affect total performance. An experiment has been designed to investigate the performance of a PV panel under various highly non-uniform temperature and irradiance profiles, generated by artificial lighting. Measurements of irradiance and temperature distribution are related to measured I–V curves and used as input to the five-parameter model. The results show the limitations of the model to emulate the PV response under such extreme conditions and provide useful insights about the effect of the temperature profile on the PV performance.

Suggested Citation

  • Petrakis Thomas & Aphrodite Ktena & Panagiotis Kosmopoulos & John Konstantaras & Michael Vrachopoulos, 2023. "Impact of Non-Uniform Irradiance and Temperature Distribution on the Performance of Photovoltaic Generators," Energies, MDPI, vol. 16(17), pages 1-20, August.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6322-:d:1229894
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    References listed on IDEAS

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    1. Abbassi, Rabeh & Abbassi, Abdelkader & Jemli, Mohamed & Chebbi, Souad, 2018. "Identification of unknown parameters of solar cell models: A comprehensive overview of available approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 453-474.
    2. Nouha Mansouri & Abderezak Lashab & Dezso Sera & Josep M. Guerrero & Adnen Cherif, 2019. "Large Photovoltaic Power Plants Integration: A Review of Challenges and Solutions," Energies, MDPI, vol. 12(19), pages 1-16, October.
    3. Celik, Ali Naci & Acikgoz, NasIr, 2007. "Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four- and five-parameter models," Applied Energy, Elsevier, vol. 84(1), pages 1-15, January.
    4. Gökmen, Nuri & Hu, Weihao & Hou, Peng & Chen, Zhe & Sera, Dezso & Spataru, Sergiu, 2016. "Investigation of wind speed cooling effect on PV panels in windy locations," Renewable Energy, Elsevier, vol. 90(C), pages 283-290.
    5. Chenni, R. & Makhlouf, M. & Kerbache, T. & Bouzid, A., 2007. "A detailed modeling method for photovoltaic cells," Energy, Elsevier, vol. 32(9), pages 1724-1730.
    6. Karim Menoufi, 2017. "Dust Accumulation on the Surface of Photovoltaic Panels: Introducing the Photovoltaic Soiling Index (PVSI)," Sustainability, MDPI, vol. 9(6), pages 1-12, June.
    Full references (including those not matched with items on IDEAS)

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