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PV Temperature Prediction Incorporating the Effect of Humidity and Cooling Due to Seawater Flow and Evaporation on Modules Simulating Floating PV Conditions

Author

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  • Socrates Kaplanis

    (Laboratory of Soft Energy Applications and Environmental Protection, University of West Attica, 12201 Athens, Greece)

  • Eleni Kaplani

    (School of Engineering, Faculty of Science, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK)

  • John K. Kaldellis

    (Laboratory of Soft Energy Applications and Environmental Protection, University of West Attica, 12201 Athens, Greece)

Abstract

The temperature prediction for floating PV (FPV) must account for the effect of humidity. In this work, PV temperature prediction for steady-state T pv and transient conditions T pv (t) incorporates the effect of humidity and cooling due to seawater (s.w.) splashing and evaporation on PV modules. The proposed formulas take as main inputs the in-plane solar irradiance , wind speed, ambient temperature, relative humidity (RH), and s.w. temperature. The transient effects of s.w. splashing and the evaporation of the s.w. layer from the module are theoretically described considering the layer’s thickness using Navier–Stokes equations. T pv and T pv (t) measurements were taken before and after s.w. splashing on c-Si modules at the seashore and inland. PV temperature predictions compared to measured values showed very good agreement. The 55% RH at the seashore versus 45% inland caused the T pv to decrease by 18%. The T pv (t) at the end of the s.w. flow of 50–75 mL/s/m on the module at the seashore was 35–51% lower than the T pv inland. This T pv (t) profile depends on the s.w. splashing, lasts for about 1 min, and is attributed to higher convection, water cooling, and evaporation on the modules. The PV efficiency at FPV conditions was estimated to be 4–11.5% higher compared to inland.

Suggested Citation

  • Socrates Kaplanis & Eleni Kaplani & John K. Kaldellis, 2023. "PV Temperature Prediction Incorporating the Effect of Humidity and Cooling Due to Seawater Flow and Evaporation on Modules Simulating Floating PV Conditions," Energies, MDPI, vol. 16(12), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:12:p:4756-:d:1172617
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    References listed on IDEAS

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    Cited by:

    1. Shahad Mohammed Radhi & Sadeq D. Al-Majidi & Maysam F. Abbod & Hamed S. Al-Raweshidy, 2024. "Machine Learning Approaches for Short-Term Photovoltaic Power Forecasting," Energies, MDPI, vol. 17(17), pages 1-23, August.
    2. Maarten Dörenkämper & Minne M. de Jong & Jan Kroon & Vilde Stueland Nysted & Josefine Selj & Torunn Kjeldstad, 2023. "Modeled and Measured Operating Temperatures of Floating PV Modules: A Comparison," Energies, MDPI, vol. 16(20), pages 1-18, October.
    3. Monica Nicola & Matthew Berwind, 2024. "Improving Module Temperature Prediction Models for Floating Photovoltaic Systems: Analytical Insights from Operational Data," Energies, MDPI, vol. 17(17), pages 1-17, August.

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