Optimization of Maintenance of PV Module Arrays based on Asset Management Strategies: Case of Study

This paper presents a methodology to optimize the maintenance of grid-connected photovoltaic (PV) systems by defining cleaning intervals within an asset management framework. The approach combines analysis of energy production, feed-in tariffs, and cleaning costs to maximize overall revenue. The proposed approach was evaluated through a case study of a 5.6 kWp PV system located on the Bogotá campus of the Universidad Nacional de Colombia. Experimental results showed that modules without cleaning accumulated performance losses above 25–30% after five years, while those cleaned annually exhibited controlled losses of around 5–10% per year. Furthermore, the variability of the loss rate (LR) highlights the importance of adapting soiling models to local climates. In Bogotá, where rainfall is frequent, precipitation contributes to partial self-cleaning, reducing soiling accumulation compared to arid climates. The study concludes that incorporating local environmental factors into predictive models and maintenance planning improves both the technical performance and economic profitability of PV systems.