SIROCO

SIROCO is an advanced predictive maintenance system for photovoltaic plants that combines artificial intelligence with thermal, hyperspectral, and multispectral imaging technologies. The developed solutions include digital twins of the installations, using production and meteorological data to detect performance deviations and anticipate potential failures. To manage and process the vast amount of data generated, SIROCO employs IoT platforms that centralize the information and facilitate real-time analysis and visualization of the results.

Additionally, the system involves work with drones equipped with thermal, hyperspectral, and multispectral sensors, capable of detecting dust and salt accumulations on the panels, as well as early signs of corrosion on metal structures. Through computer vision algorithms, it processes the data obtained from flight campaigns and determines the impact on production, in combination with digital twin algorithms.

The solutions will be tested in real photovoltaic plants, both in large-scale plants in the Canary Islands and small-scale installations at ITG’s experimental facilities in Galaxy Lab, to validate their effectiveness in multiple operational environments affected by corrosion or salt problems.

With its dual approach based on data and computer vision, SIROCO optimizes the maintenance of photovoltaic plants, improving efficiency and maximizing plant production.