An accurate thermal model for the PV electric generation prediction: long-term validation in different climatic conditions. (January 2021)

• Record Type: Journal Article
• Authors: Bevilacqua, Piero; Perrella, Stefania; Bruno, Roberto; Arcuri, Natale
• Is Part Of: Renewable energy. Volume 163(2021)
• Page Start: 1092
• Page End: 1112
• Publication Date: 2021-01
• Subjects: PV thermal Model -- Experimental validation -- PV temperature Prediction -- Actual efficiency -- PV electric Power prediction; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2020.07.115
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Solar radiation incident on photovoltaic modules only partly directly convert into electricity; the rest is converted into heat that increases the module layers' temperature. In order to quantify both the output power and the electrical efficiency, the knowledge of the temperature profile is essential. This study proposes a transient one-dimensional thermal model of photovoltaic modules which provides the temperature distribution across the panel thickness, used to predict the electricity production under variable operating weather conditions. The model was implemented and validated considering the module back surface temperature and the produced electric power measured in an experimental set-up located at the University of Calabria (Italy). A more detailed evaluation of the long-wave radiative heat exchange between the front glass cover and the external environment is considered, employing experimental sky temperatures data. Different formulations of the heat transfer coefficient were tested to provide more accurate results. To show the reliability of the model predictions over a wide range of operating conditions, the validation was conducted considering several days of each season with different meteorological situations. The accuracy of the model was proved by statistical parameters showing the excellent agreement between the predicted and measured temperatures and power outputs. Highlights: One-dimensional thermal model for photovoltaic modules was developed. A new formulation for sky temperature was used. Comparison with experimental data of surface temperature and electric output. A seasonal validation was developed in different meteorological conditions. An excellent accuracy in predictions was found in terms of correlation indexes.