Quantifying the benefits of PV module shading for building heat gain reduction: A machine learning approach

Abstract

This study investigates the indirect benefit due to the shading effect from PV rooftop systems installed on building envelopes by proposing a new method based on a machine-learning algorithm. The study gathered a year of data from a 25 kWp PV rooftop system installed on a metal sheet roofing. It classifies the dataset into four categories based on solar irradiance and ambient temperature to represent Thailand's climate. There evaluated the RTTV and case study from implemented projects with metal sheet roofing in Thailand to estimate the potential electricity bill savings from the PV module shade effect. The results reveal an inverse relationship between the percentage of heat reduction and heat gain reduction, with the most significant reduction occurring under high solar irradiance and ambient temperature conditions. The shading effect caused by the PV modules provides an indirect benefit of approximately 38 kWh/kWp/year from electricity bill savings. In contrast, the PV system production yields around 1401 kWh/kWp/year based on radiation of about 1839 kWh/m2/year. The study estimates that energy-saving possibilities range from 0.038 to 0.052 kWh/m2/day, depending on the weather conditions, equivalent to an electricity saving of approximately 6.33 kWh/m2/year from air conditioner use.