Soiling assessment and cleaning decision analysis for a photovoltaic feasibility study: a case study in a high dust-loaded mining environment

• One-year soiling campaign at a Moroccan mine showed 0.30%/day rate and 5.8% loss • Dynamic cleaning combines soiling, weather, and economics for optimal decisions • Dynamic cleaning yields $230k gain and +2.6 pp net revenue with 14 cleanings/year • It outperforms the best fixed and threshold-based cleaning by +1.1 pp and +0.1 pp • Dynamic cleaning gives highest NPV ($82.27 M, +4.1%) using market electricity price Soiling of photovoltaic (PV) modules remains a major operational challenge, as it lowers energy yield and financial performance. Although regular cleaning mitigates soiling losses, selecting an appropriate cleaning strategy is critical, since suboptimal decisions may lead to unnecessary energy losses or excessive operational costs. This study presents a one-year soiling and meteorological measurement campaign conducted as part of a feasibility study for a large-scale PV project at a mining site in Morocco. Ground-based measurements are integrated into a performance model of a simulated 44 MWp PV power plant. Results show an average daily soiling rate (ΔSR) of 0.30%/day, resulting in an annual energy loss of 4,442 MWh (100.9 MWh/MWp), equivalent to 5.8% of potential energy production. A dynamic cleaning decision approach has been employed, combining soiling levels, weather conditions, and economic factors to optimize cleaning timing. Cleaning is triggered only when the projected energy recovery outweighs the associated cleaning expenses. The proposed dynamic cleaning strategy reduces losses to 1.9%, recovering 2,990 MWh annually and generating an economic gain of approximately $230,000 ($5.23/kW/year) relative to the no-cleaning scenario. Compared to the best fixed-frequency and threshold-based approaches, the dynamic approach increases net revenue by 1.1 and 0.1 percentage points, respectively, demonstrating its effectiveness for practical PV operation and feasibility assessment. In addition, a detailed economic analysis based on Levelized Cost of Electricity and Net Present Value has been performed to further evaluate the financial viability of the proposed strategy.