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PV temperature and performance prediction in free-standing, BIPV and BAPV incorporating the effect of temperature and inclination on the heat transfer coefficients and the impact of wind, efficiency and ageing

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  • Kaplanis, S.
  • Kaplani, E.
  • Kaldellis, J.K.

Abstract

A novel compact model is developed to predict the PV temperature Tpv, coefficient f which relates Tpv with the in-plane solar irradiance IT, and power output Pm. The Tpv, IT, ambient temperature Ta, and wind velocity vw on a sun-tracking pc-Si PV and c-Si BIPV were monitored. f depends explicitly on vw, PV efficiency, heat losses coefficient, and implicitly on Tpv, IT, Ta, loosely on the module inclination at low vw, while this effect weakens at high vw. Tpv prediction is provided by means of 5 functions, which cater for the deviation of the environmental conditions from the Standard Operating Conditions, the operating efficiency, the natural ageing, PV geometry and cell technology. The Tpv prediction for the sun-tracking system has relative error 2.6% for PV operating temperatures around the NOCT, and may overestimate by up to 1.4 °C. Similarly, the relative error for the BIPV system is −2.1% for PV temperatures around the NOCT, with underestimation up to 1.6 °C. The model predicted Pm with relative error 1.9% for PV operating near its nominal value. The model is compared to 3 well-known models and also applied to other BIPV/BAPV configurations in various countries proving its wide applicability, high accuracy and universality.

Suggested Citation

  • Kaplanis, S. & Kaplani, E. & Kaldellis, J.K., 2022. "PV temperature and performance prediction in free-standing, BIPV and BAPV incorporating the effect of temperature and inclination on the heat transfer coefficients and the impact of wind, efficiency a," Renewable Energy, Elsevier, vol. 181(C), pages 235-249.
    • Handle: RePEc:eee:renene:v:181:y:2022:i:c:p:235-249
    DOI: 10.1016/j.renene.2021.08.124
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    References listed on IDEAS

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    1. Wu, Zhenghong & Zhang, Ling & Su, Xiaosong & Wu, Jing & Liu, Zhongbing, 2022. "Experimental and numerical analysis of naturally ventilated PV-DSF in a humid subtropical climate," Renewable Energy, Elsevier, vol. 200(C), pages 633-646.
    2. 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.
    3. Žižak, Tej & Domjan, Suzana & Medved, Sašo & Arkar, Ciril, 2022. "Efficiency and sustainability assessment of evaporative cooling of photovoltaics," Energy, Elsevier, vol. 254(PA).
    4. Maturo, Anthony & Buonomano, Annamaria & Athienitis, Andreas, 2022. "Design for energy flexibility in smart buildings through solar based and thermal storage systems: Modelling, simulation and control for the system optimization," Energy, Elsevier, vol. 260(C).
    5. Ateş, Ali Murat, 2022. "Unlocking the floating photovoltaic potential of Türkiye's hydroelectric power plants," Renewable Energy, Elsevier, vol. 199(C), pages 1495-1509.

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