Customized Cleaning Solutions for Photovoltaic Fleets: Integrating Soiling Modeling and Optimization Techniques

This research addresses the need for optimized cleaning schedules within PV fleets, especially in regions like the United Arab Emirates with high dust accumulation. By integrating a soiling model with optimization techniques, tailored cleaning schedules for various PV systems are developed, accounting for environmental conditions, operational costs, and system attributes. Frequent cleanings maintain optimal performance but lead to higher operational costs, while infrequent cleanings can reduce efficiency. Therefore, it is essential to minimize unnecessary cleaning expenses. The analysis reveals significant variations in soiling rates over time, primarily driven by seasonal factors. The resulting optimized schedules outperform fixed cleaning policies, yielding an 8% profit increase and a 6% efficiency enhancement. Emphasizing alignment of cleaning schedules with system characteristics advances performance and resource management in PV technologies. Future research should focus on obtaining real-world data and employing forecasting techniques for accurate predictions of soiling levels and their impact on PV system efficiency.