Impact of Dust Accumulation on Solar Panel Performance: A Predictive Approach Using Regression Models

The accumulation of dust is responsible for significant changes in output power and electrical characteristics on solar panels. This study determines the effect of dust volume on panel performance, particularly on current and power output, through experimental results and predictive models. Several regression techniques, including linear, polynomial, and exponential models, were used, along with machine learning approaches. Performance evaluations were performed using RMSE for model comparison to determine the most accurate model. The results emphasize the power of such sophisticated predictive models to develop optimization solutions in solar panel maintenance by predicting power loss due to soiling. In general, this study contributes to the creation of data-driven approaches to improve performance and durability in photovoltaic systems.