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Energies by Jose Feliciano Ibañez Quiroz is a document available to read on EtoBox.

This study analyzes the panel temperature dependence on atmospheric parameters at a photovoltaic park in semi-arid Chile using Artificial Neural Networks (ANNs). The ANN model demonstrated superior prediction accuracy with a Root Mean Squared Error (RMSE) of 1.59 °C compared to traditional deterministic models, with air temperature being the most influential factor. The research highlights the potential of ANNs for improving the prediction of photovoltaic panel temperatures in arid regions.

Author

Jose Feliciano Ibañez Quiroz

Language

EN