The consultancy DNV GL has published its latest document “Making renewable energies smarter: benefits, risks and future of artificial intelligence in solar and wind energy”, in which it predicts a growing use of Artificial Intelligence (AI), for which it foresees a $ 3 trillion market by 2024, across the industry, in which it analyzes its current and future potential to accelerate processes in multiple areas of renewable energy development.

The report focuses on the downstream sector and notes that wind and solar plants have already benefited from the widespread development of sensor technology and data analytics. “We look forward to the installation of more sensors, the growth of easier-to-use machine learning tools, and the continued expansion of data analysis, processing and analytics capabilities to create new operational efficiencies,” said Lucy Craig, Director of Technology and Innovation at DNV GL.

The paper expects solar and wind power to further harness the benefits of artificial intelligence in the areas of inspection and troubleshooting, where “autonomous drones with real-time AI support analytics” and “crawling robots that can get close to the surface of a structure”. Ultrasonic transmission, which can be used to penetrate structures and reveal material flaws, will pay off.

Planning and due diligence is another area that DNV GL says can benefit from the increased use of AI: “planning and analysis that today can require many human hours and thousands of documents can be greatly reduced in the future and even improved” .

DNV GL even speaks of a future in which the construction of wind and solar plants will be fully automated and carried out by ‘autonomous driving robots, which in the future may build entire terrestrial or solar wind farms: parts of a wind turbine or solar panels are transported from the factory by autonomous trucks, unloaded by another set of robots, attached to the foundations that other robots have excavated and filled, and assembled by a final set of robots and drones ”.

Despite all this potential, DNV GL points out the risks of such approaches and the danger of relying too heavily on artificial intelligence rather than the deep insights needed to manage such a system. “For the majority of participants in the renewable energy industry,” states the DNV GL press release, “building stable, progressive and reliable artificial intelligence systems requires knowledge and data sets from many different projects.”