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Thermo-electrical performance assessment of a partially submerged floating photovoltaic system

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  • Elminshawy, Nabil A.S.
  • Osama, Amr
  • Saif, Amany M.
  • Tina, Giuseppe Marco

Abstract

The floating photovoltaic (FPV) is characterized by the possibility to keep the PV cell at a reduced temperature compared to Land-Based Photovoltaic (LBPV) but this reduction is not so large. However, in hot climate, the working temperature of the FPV could rise enough to act negatively on the productivity. The present article focuses on assessing the performance of a partially submerged photovoltaic (PSPV) system planned to be deployed over Egypt's northern lakes. The PSPV is a new modification of the FPV system that was experimentally investigated under the Egyptian weather conditions in the present study. The above PSPV module was tested with various submerged ratios (y) of 5, 10, and 20%, defined as the ratio of the submerged portion to the module's length. It was concluded that the average surface temperatures of the PSPV module were lower than those of the reference LBPV module. By reducing the working temperature of the PSPV module at (y = 10%) by 11.10%, a power gain of 18.20% over the LBPV module was achieved. The cost per unit of produced electricity (LCOE) for the PSPV module was reduced by 7.52%, from 0.063 to 0.059 ($/kWh), by raising the submerged ratio from 5% to 10%.

Suggested Citation

  • Elminshawy, Nabil A.S. & Osama, Amr & Saif, Amany M. & Tina, Giuseppe Marco, 2022. "Thermo-electrical performance assessment of a partially submerged floating photovoltaic system," Energy, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:energy:v:246:y:2022:i:c:s0360544222003474
    DOI: 10.1016/j.energy.2022.123444
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    References listed on IDEAS

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    1. Choi, Seok Min & Park, Chang-Dae & Cho, Sung-Hoon & Lim, Byung-Ju, 2022. "Effects of wind loads on the solar panel array of a floating photovoltaic system – Experimental study and economic analysis," Energy, Elsevier, vol. 256(C).
    2. Ghandehariun, Samane & Ghandehariun, Amir M. & Ziabari, Nima Bahrami, 2023. "Performance prediction and optimization of a hybrid renewable-energy-based multigeneration system using machine learning," Energy, Elsevier, vol. 282(C).
    3. Elminshawy, Nabil A.S. & El-Damhogi, D.G. & Ibrahim, I.A. & Elminshawy, Ahmed & Osama, Amr, 2022. "Assessment of floating photovoltaic productivity with fins-assisted passive cooling," Applied Energy, Elsevier, vol. 325(C).

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