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Modeled and Measured Operating Temperatures of Floating PV Modules: A Comparison

Author

Listed:
  • Maarten Dörenkämper

    (TNO Energy and Materials Transition, High Tech Campus 21, 5656 AE Eindhoven, The Netherlands)

  • Minne M. de Jong

    (TNO Energy and Materials Transition, High Tech Campus 21, 5656 AE Eindhoven, The Netherlands)

  • Jan Kroon

    (TNO Energy and Materials Transition, High Tech Campus 21, 5656 AE Eindhoven, The Netherlands)

  • Vilde Stueland Nysted

    (Department of Solar Power Systems, Institutt for Energiteknikk (IFE), Insituttveien 18, 2007 Kjeller, Norway)

  • Josefine Selj

    (Department of Solar Power Systems, Institutt for Energiteknikk (IFE), Insituttveien 18, 2007 Kjeller, Norway)

  • Torunn Kjeldstad

    (Department of Solar Power Systems, Institutt for Energiteknikk (IFE), Insituttveien 18, 2007 Kjeller, Norway)

Abstract

The power output of a photovoltaic system is dependent on the operating temperature of the solar cells. For floating PV (FPV), increased wind speeds can result in increased yield due to lowered operating temperatures, which has long been stated as a key advantage for FPV. So far, this effect has not been included in commercial software packages for yield estimation. Typically, only standard settings are provided, taking into account the mounting type (PVsyst) or mounting and module type (Sandia). This may result in an underestimation of the yield, and consequently, the estimated Levelized Cost of Electricity (LCOE) of the FPV project. In this study, a linkage between recorded module temperatures from FPV systems located in The Netherlands and Sri Lanka and the prevalent models employed within PVsyst and Sandia software for estimating module temperatures are established. Our findings reveal that the models within PVsyst and Sandia tend to overestimate module temperatures by 2.4% and 3%, respectively, for each 1 m/s increment in wind speed. We present two methods for determining the single heat loss coefficient, or U-value, tailored to specific sites accounting for local wind conditions. The first method computes the U-value based on the average monthly wind speed, whereas the second employs the irradiance-weighted average monthly wind speed. The latter method can be advantageous for locations characterized by significant fluctuations in wind speeds between night and day. Through a statistical residual analysis comparing measured and modeled module temperatures, we demonstrate that our proposed methods offer a more accurate representation of module temperature compared to the PVsyst and Sandia models when default settings are used. When we subsequently compute the specific yield using both measured and modeled temperatures, we observe that the approach using irradiance-weighted average wind speed shows a higher yield of up to 2% compared to the traditional methods.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7153-:d:1263000
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
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