Abstract:

In this study, Artificial Neural Network model (ANN) has been used to model the temperature dependent current, voltage and output power characteristics of uncooled and cooled photovoltaic panels. In the previous laboratory experiment, the current and voltage values produced by the photovoltaic panels in the temperature range of 20 ˚C- 65 ˚C for one hour were measured. Models have been created using the Artificial Neural Network technique with experimental data containing 60 samples for each of these three PV/T, including uncooled and two different cooled models. The combinations and features of the Artificial Neural Network model that provide the lowest model error have been achieved. The performance of the Neural Network model performed well in both the uncooled photovoltaic, cooled with flat fins/PCM and cooled with perforated fins/PCM, with RMSE model errors of 1.15e-02, 6.76e-03 and 6.10e-03, respectively. Therefore, it was suggested as a potent tool for modeling current, voltage, and generated power at all temperatures reached during the hour-long experiment.

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