Online application of the periodic linear regression method for daily monitoring of photovoltaic systems performance

This paper presents an analysis of the performance of photovoltaic (PV) systems using daily applications of the periodic linear regression method to the performance indicators Final Yield (YF) and Reference Yield (YR). The research was conducted on PV systems installed on rooftops and ground at the Federal Institute of Education, Science, and Technology of Goiás (IFG), Itumbiara Campus, from July 2022 to August 2023. The Energy Monitoring and Management Software (SMGE) was developed to calculate the performance indicators and perform linear regression to analyze the performance of the systems. The results demonstrate that the efficiency of the systems can be monitored by analyzing variations in the slopes of the linear regression lines. An increase in energy conversion efficiency was observed following the cleaning of the PV panels, as reflected in significant changes in the regression slopes. Additionally, natural events, such as rainfall, positively impacted system efficiency. These findings highlight the importance of proper maintenance of PV panels, whether through scheduled cleaning or natural events like rain.