Artificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time. () will increasingly automate operations over the next several years in the solar and wind industries and boost efficiencies across the renewable energy sector, according to a new DNV GL position paper.
The position paper “ Making Renewables Smarter: The benefits, risks, and future of artificial intelligence in solar and wind, ” explores where artificial intelligence like machine will have an impact to increase efficiencies in the renewables industry. Areas include decision making and planning, condition monitoring, , inspections, certifications, and supply chain optimization, but also the way technical work is carried out.
The renewables industry is a data-rich environment. Wind and solar generation plants have beneﬁted from the fact that these technologies have been commercially developed relatively recently and have had sensor technology installed from the beginning. As a result, most of the advances supported by artificial intelligence have been in resource forecasting, control, and predictive maintenance. DNV GL‘s paper outlines how these advances are likely to progress further.
“We expect the installation of more sensors, the increase in easier-to-use machine tools, and the continuous expansion of data monitoring, processing and analytics capabilities to create new operating efficiencies — and new and disruptive business models,” commented Lucy Craig, Director Technology and Innovation at DNV GL – Energy.
Solar and wind industry stakeholders will see artificial intelligence benefits in several areas, including:
- growing in prevalence for remote inspection, with new benefits in maintenance and troubleshooting.
- Crawling robots that can get close to a structure’s surface enabling a new set of technologies such as microwave and ultrasonic transmitters and receivers, which can be used to penetrate structures to reveal faults in materials.
- Supply chain optimizations by robots, which can in future build entire onshore wind or solar farms: parts of a wind turbine or a solar array are transported from the factory by self-driving lorries, unloaded by another set of robots, attached to the foundations that yet other robots have dug and filled, and pieced together by a final set of robots and Drones are defined as unmanned aircrafts, they can be very small or rather large. Most drones cannot operate completely autonomous, but need human inputs. Moreover, there are a lot of laws in place which do not allow for private drones to fly out of sight..
- Autonomous drones with real-time artificial intelligence-supported analysis will become the primary tool for carrying out effective and efficient inspections of wind turbines and solar panels.
- applications accelerating due diligence, reducing the time investment of planning and analysis that today requires many human hours.
In addition, artificial intelligence will tend to automate decision making, driving costs out of energy development, production, and delivery in the solar and wind industries. […]