Predictive system for the presence of environmental residues and corrosion on the surface of the modules and structural system of photovoltaic plants, by means of automatic processing of thermal and hyperspectral images.
Data
Acronym: SIROCO
Reference: CPP2023-010858
Partners: University of las Palmas de Gran Canaria (ULPGC), Technological Institute of Galicia Foundation and Instituto Tecnológico y de Energías Renovables, S.A (ITER).
Duration: 01/12/2024 (36 months)
Budget: 800,171.75 €
Co-Financing: Public-Private Partnership 2023. State Plan for Scientific and Technical Research and Innovation 2021-2023. Ministry of Science and Innovation. Project CPP2023-010858 funded by MCIN/AEI /10.13039/501100011033 and by the European Union NextGenerationEU/ PRTR.
Project overview
The SIROCO project focuses on the development of an advanced system for the predictive maintenance of photovoltaic plants, combining automatic thermal, hyperspectral and multispectral image processing technologies with artificial intelligence. This system will detect and prevent problems such as the accumulation of environmental pollutants (dust and saltpetre) in the photovoltaic modules and corrosion in the metal support structures, which affect the energy efficiency and integrity of these installations.
Using drones equipped with advanced sensors and the integration of meteorological data and historical performance, SIROCO proposes an innovative solution to identify and anticipate risks in an accurate and non-invasive way. The integration of these technologies will allow not only an accurate diagnosis of current problems, but also the ability to predict future challenges based on historical data and weather projections. This predictive approach is fundamental to the development of proactive maintenance strategies, minimising corrective interventions, maximising the efficiency and lifetime of PV installations, and thereby reducing maintenance costs.
The project will employ a combination of innovative technologies. It will use measurement strings on PV panels to monitor their performance in real time, drones equipped with thermal and RGB sensors to fly over the installations and detect the presence of dust and saltpetre on the panels. In addition, hyper- and multi-spectral sensors will be incorporated specifically for detecting signs of corrosion on the supporting metal structures.
In summary, the project represents a step forward in the management and maintenance of photovoltaic plants, offering an innovative model that combines the latest technology in RGB, thermal and hyper/multispectral imaging with predictive analytics to ensure maximum efficiency and durability of these important renewable energy sources.
The SIROCO project (CPP2023-010858) will last 36 months and is funded by the Ministry of Science and Innovation and the State Research Agency (10.13039/501100011033) and by the European Union in the framework of the EU’s Next Generation EU Recovery Plan and Spain’s Recovery, Transformation and Resilience Plan (PRTR).
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