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Dynamic Electro-Thermal PV Temperature and Power Output Prediction Model for Any PV Geometries in Free-Standing and BIPV Systems Operating under Any Environmental Conditions

Author

Listed:
  • Eleni Kaplani

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

  • Socrates Kaplanis

    (Renewable Energy Systems Lab, University of Peloponnese, 26334 Patra, Greece)

Abstract

PV temperature significantly affects the module’s power output and final system yield, and its accurate prediction can serve the forecasting of PV power output, smart grid operations, online PV diagnostics and dynamic predictive management of Building Integrated Photovoltaic (BIPV) systems. This paper presents a dynamic PV temperature prediction model based on transient Energy Balance Equations, incorporating theoretical expressions for all heat transfer processes, natural convection, forced convection, conduction and radiation exchanges between both module sides and the environment. The algorithmic approach predicts PV temperature at the centre of the cell, the back and the front glass cover with fast convergence and serves the PV power output prediction. The simulation model is robust, predicting PV temperature with high accuracy at any environmental conditions, PV inclination, orientation, wind speed and direction, and mounting configurations, free-standing and BIPV. These, alongside its theoretical basis, ensure the model’s wide applicability and clear advantage over existing PV temperature prediction models. The model is validated for a wide range of environmental conditions, PV geometries and mounting configurations with experimental data from a sun-tracking, a fixed angle PV and a BIPV system. The deviation between predicted and measured power output for the fixed-angle and the sun-tracking PV systems was estimated at ?1.4% and 1.9%, respectively. The median of the temperature difference between predicted and measured values was as low as 0.5 °C for the sun-tracking system, and for all cases, the predicted temperature profiles were closely matching the measured profiles. The PV temperature and power output predicted by this model are compared to the results produced by other well-known PV temperature models, illustrating its high predictive capacity, accuracy and robustness.

Suggested Citation

  • Eleni Kaplani & Socrates Kaplanis, 2020. "Dynamic Electro-Thermal PV Temperature and Power Output Prediction Model for Any PV Geometries in Free-Standing and BIPV Systems Operating under Any Environmental Conditions," Energies, MDPI, vol. 13(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4743-:d:412210
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    References listed on IDEAS

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    1. Socrates Kaplanis & Eleni Kaplani, 2018. "A New Dynamic Model to Predict Transient and Steady State PV Temperatures Taking into Account the Environmental Conditions," Energies, MDPI, vol. 12(1), pages 1-17, December.
    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. Mattei, M. & Notton, G. & Cristofari, C. & Muselli, M. & Poggi, P., 2006. "Calculation of the polycrystalline PV module temperature using a simple method of energy balance," Renewable Energy, Elsevier, vol. 31(4), pages 553-567.
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    Cited by:

    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. 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.

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