Abstract
The rise in the surface temperature of a photovoltaic (PV) module due to solar heat significantly reduces the power generation performance of the PV system. Photovoltaic-Thermal (PVT) systems are being developed to overcome these limitations. The study discusses predicting power generation in PV and PVT systems. It identifies essential variables, such as solar radiation, relative humidity, and module surface temperature, that influence power generation. Regression equations were derived for PV and PVT. Results show that solar radiation plays a significant role in winter, while multiple factors affect summer power generation. The accuracy of power generation predictions using minimal variables is high, with PVT reaching 91.09%. The study also examines the effect of variables on power generation and the impact of environmental conditions, especially during summer and winter. It highlights the influence of flow rate on temperature and power generation in PVT systems. Overall, the research suggests that minimal variables can provide accurate power generation predictions, offering potential energy-saving strategies for buildings. The study emphasizes the significance of factors like solar radiation, surface temperature, and relative humidity in power generation and provides insights into predicting performance in different climates.
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