Comparative assessment of optimal cleaning schedules for various PV cleaning techniques

This study presents a comprehensive assessment of optimal cleaning frequencies and associated costs for photovoltaic (PV) systems using ten dust mitigation techniques under arid climatic conditions in Kandahar, Afghanistan. A techno-economic model was developed to evaluate both fixed-tilt and single-axis tracking systems. In fixed configurations, optimal annual cleaning intervals were 15.55 days for manual cleaning, 7.20 days for water-based, 6.48 days for washing trucks, 99.01 days for movable dry-cleaning, and 52.03 days for linear robots, while electrostatic and passive methods (natural, air-based, hydrophobic/hydrophilic self-cleaning) required daily cleaning due to negligible costs. Tracking systems, with a lower soiling rate constant (4.24 × 10−5 vs. 7.06 × 10−5 1/h), exhibited 6–8 % longer optimal intervals. LCOE analysis showed slight reductions across most techniques in tracking systems, with manual, water-based, and linear robot cleaning dropping from $0.00463 to $0.00430, $0.00210 to $0.00198, and $0.01594 to $0.01479 per kWh, respectively. Electrostatic and passive techniques remained the most economical, at $0.00013/kWh or zero. The developed framework links environmental conditions with economic performance, offering a replicable tool for optimizing PV maintenance in resource-constrained, dust-prone regions. Future research should integrate real-time soiling sensors and extend analyses across seasons to improve year-round applicability.