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Innovation and Photovoltaics: solar advanced diagnostics and predictive maintenance

4 min.

Innovation and Photovoltaics: solar advanced diagnostics and predictive maintenance

Technological innovation to support the human eye: an integrated portfolio of solutions used by Enel Green Power to revolutionize how we approach predictive diagnostics.

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Digital technologies play a key role in supporting the diagnostics of renewable plants, making it more effective and reliable.  The identification of irregularities, before they can cause failures or inefficiencies, is one of the most interesting challenges for Enel Green Power’s Innovation department.

Through algorithms and systems of big data analytics, we can extract valuable information, not directly accessible with conventional techniques, in order to guarantee efficient service and optimize maintenance times and costs, avoiding risks to people and machine failures.

Data availability is just one piece of a larger network made up of sensors, the Internet of Things, resilient connectivity systems, artificial intelligence and robots that can perform inspection missions, either in support or in place of workers in the field, in places that are difficult to access or in very large inspection areas.

These are all ingredients in the success story that features innovation in photovoltaic technologies. Through the Open Innovation model adopted by Enel Green Power, this story involves some of the top players in the world developing innovative solutions in this field.


Raptor Maps: Artificial Intelligence to Aid Solar Energy

Take, for example, the diagnostic software solution for solar plants developed by Raptor Maps, a US company active in the field of artificial intelligence. Through this collaboration, EGP has implemented an innovative system able to detect irregularities on photovoltaic panels in its solar fleet faster and more easily than before.

By using drones equipped with thermal imaging cameras, we can inspect vast areas and acquire panel temperature data. The data collected via aerial inspections, together with other information from the photovoltaic fields, is analyzed and turned into detailed reports, able to identify any incipient breakdowns before they lead to worse situations.


ARP: A Robot on the Ground and a Drone in the Sky

The path to advanced diagnostics also involves startups, such as M2D and Etnamatica, young innovative startups founded on the slopes of Mt. Etna in Italy.

From Enel Green Power’s Innovation Lab in Catania comes ARP (Autonomous Robot Platform for renewable plants), a robotic system for advanced diagnostics, which is able to identify irregularities in photovoltaic modules through computer vision algorithms.

The system uses a self-driving land rover, equipped with a drone base, which is also self-driving and tethered, meaning it is connected with a cable, to guarantee greater autonomy, higher resolution and efficiency.

The ARP system is able to identify inconsistencies in photovoltaic modules through a computer vision algorithm that analyzes images from the drone, working in symbiosis and constant communication with the land rover. The robot rover and drone are robotic eyes and ears that let us detect what the human eye would not be able to recognize in the same timeframe or with the same level of detail.


The Advantages of Innovation

These innovative solutions allow for a sharp reduction in inspection times for large-scale plants, in some cases going from 200 days with conventional methods to just 13 days, as well as savings on maintenance costs. Digital transformation and technological innovation prove to be a winning combination to guarantee the rapid and safe development of renewable energy. 

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