Soiling estimation methods in solar photovoltaic systems: Review, challenges and future directions

Abstract

• Soiling cuts solar energy yield by 20–50 % in desert regions due to dust exposure. • Direct soiling measurements are accurate but costly; indirect methods scale better. • Hybrid techniques combining optical & meteorological data improve soiling estimates. • ML models use sensor & performance data to optimize cleaning and maximize output. • Lack of standardized measurement protocols hampers global soiling data comparison. Soiling, the accumulation of dust and particulate matter on solar photovoltaic (PV) panels, reduces their efficiency, energy yield, and increases operational costs, particularly in dust-prone regions. This review critically examines methods for estimating soiling losses, focusing on approaches to accurately quantify dust accumulation. It explores direct methods such as gravimetric, optical, and imaging techniques, which offer high accuracy but face challenges in scalability, cost, and environmental sensitivity . Indirect methods, including Performance Ratio (PR) analysis and meteorological models, provide scalable, cost-effective solutions but often lack precision due to confounding factors like shading and system degradation . Hybrid models that integrate both direct and indirect techniques improve accuracy but require substantial data and computational resources. A major challenge identified in the review is th e lack of standardized protocols for soiling measurement, making comparisons across studies and regions difficult. The review emphasizes the importance of real-time monitoring , machine learning integration for predictive maintenance , and the development of anti-soiling coatings and self-cleaning technologies. Long-term studies across diverse climates are needed to create universally applicable soiling estimation models. By addressing these challenges and advancing existing technologies, the solar industry can more effectively estimate soiling losses, enhance PV system efficiency, and contribute to achieving global sustainability goals, particularly SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action) .