Optimizing PV maintenance: Methods, cleaning frequency, and a selection protocol

Abstract

Dust accumulation significantly reduces the efficiency of Photovoltaic (PV) systems, with energy losses reaching up to 50% in arid and semi-arid regions. This study presents a comprehensive review of PV cleaning methods, analyzing both passive (natural mitigation, coated surfaces, architectural solutions) and active methods (manual cleaning, water-based systems, electromechanical techniques, robotic cleaning, and piezoelectric approaches). A systematic evaluation of their operational principles, effectiveness, and economic implications is conducted, considering environmental constraints and site-specific conditions. A key contribution of this study is the assessment of optimal cleaning frequency, identifying how climatic and geographical factors influence maintenance schedules. Additionally, a novel Strategic PV Cleaning Optimization Method (SPV-COM) is introduced, offering a structured, multi-criteria decision-making framework to compare and rank cleaning methods based on technical performance, economic feasibility, and long-term sustainability. This methodology integrates operational costs and maintenance requirements to ensure an adaptive selection process that aligns with real-world PV installations. The proposed framework is scalable and applicable to diverse PV cleaning technologies, supporting decision-making in both small-scale and large-scale installations. The findings highlight, for example, the economic trade-offs between water-intensive methods and emerging autonomous solutions, as well as the need for region-specific strategies. By addressing critical gaps in prior studies, this work provides a structured approach to optimizing PV maintenance, contributing to improved efficiency, cost reduction, and sustainable energy production. • Framework to optimize PV cleaning based on technical and local conditions. • Comparative review of passive and active mitigation strategies for soiling. • Decision matrix ranks methods using cost, efficiency and environmental impact. • Novel SPVCOM model supports cleaning frequency and method selection. • Results show trade-offs among efficiency, cost and sustainability of methods.