Adapting Thermal Models for Photovoltaic Systems in Malta

Predicting the annual energy generation of photovoltaic (PV) systems is essential for ensuring both financial and infrastructural viability. This study focuses on adapting and validating a thermal model for Malta’s unique Mediterranean environment, using the National Renewable Energy Laboratory (NREL) model as a foundation. By calibrating site-specific coefficients, the model effectively predicts module and cell temperatures, enhancing performance monitoring and anomaly detection. High-resolution environmental data, spanning multiple seasons, was used for validation, demonstrating the model's robustness with a mean prediction error of -0.466°C for module temperature and 0.880°C for cell temperature, achieving over 95% accuracy. Error analysis confirmed an unbiased distribution using the Kolmogorov-Smirnov test. The outcomes contribute to improved predictive maintenance, energy yield optimization, and sustainable deployment of PV technology in challenging climates. Future efforts will focus on expanding datasets and conducting inferential statistical analyses to further generalize the findings.