Análise de modelos de estimação da temperatura de módulos fotovoltaicos aplicados para uma localidade em Fortaleza-CE

Abstract

The photovoltaic (PV) solar energy has been growing at an accelerated pace in recent years and, as a result, we seek to increasingly optimize the use of this resource. For this, knowing the temperature behavior of the PV modules is extremely important, since the increase in this parameter contributes to the reduction of the efficiency and, consequently, of the power generation. Thus, this work tested four temperature prediction models for photovoltaic cells, observing different meteorological scenarios and analyzing the influence of the wind in estimating this temperature. The models are: Standard NOCT, Ross, Skoplaki and Mattei. To do so, meteorological data measured in a location in Fortaleza-CE were applied. The sample was segmented in two different ways and the results were analyzed separately according to the segmentation criteria, which were irradiation and periods of the year. The models were further evaluated generally by segment and by each segment’s characteristic day. Finally, they were validated through statistical errors: Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Thus, it was found that the models that best fit this case were the Ross e Mattei. Furthermore, the introduction of wind considerations in the models showed to be of great relevance.