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A New Dynamic Model to Predict Transient and Steady State PV Temperatures Taking into Account the Environmental Conditions

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  • Socrates Kaplanis

    (Renewable Energy Systems Lab, Technological Educational Institute of Western Greece, M. Alexandrou 1, 26334 Patra, Greece)

  • Eleni Kaplani

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

Abstract

Photovoltaic (PV) cell and module temperature profiles, T c and T pv , respectively, developed under solar irradiance were predicted and measured both at transient and steady state conditions. The predicted and measured T c or T pv covered both a bare c-Si PV cell, by SOLARTEC, at laboratory conditions using a solar light simulator, as well as various c-Si and pc-Si modules (SM55, Bioenergy 195W, Energy Solutions 125W) operating in field conditions. The time constants, τ, of the T c and T pv profiles were determined by the proposed model and calculated using the experimentally obtained profiles for both the bare PV cell and PV modules. For model validation, the predicted steady state and transient temperature profiles were compared with experimental ones and also with those generated from other models. The effect of the ambient temperature, T a , wind speed, v w , and the solar irradiance, I T , on the model performance, as well as of the mounting geometries, was investigated and incorporated in the prediction model. The predicted temperatures had the best matching to the measured ones in comparison to those from six other models. The model developed is applicable to any geographical site and environmental conditions.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:2-:d:191969
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Sohani, Ali & Cornaro, Cristina & Shahverdian, Mohammad Hassan & Hoseinzadeh, Siamak & Moser, David & Nastasi, Benedetto & Sayyaadi, Hoseyn & Astiaso Garcia, Davide, 2023. "Thermography and machine learning combination for comprehensive analysis of transient response of a photovoltaic module to water cooling," Renewable Energy, Elsevier, vol. 210(C), pages 451-461.

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