Terna has initiated a collaboration with Eoliann e Fast Computing, two startups chosen for the “Data Science for Resilience” challenge. Launched in December last year, "Data Science for Resilience" is the first call to be launched by the manager of the national electricity grid on the open innovation platform "Terna Ideas" and saw the participation of 71 startups. In detail, the applications concerned solutions based onartificial intelligence to further improve predictive maintenance and monitoring of electrical infrastructure, with the aim of making them even safer and more efficient in the face of increasingly extreme and frequent climate events.
“We are very satisfied with the participation and the great enthusiasm with which the startups responded to this challenge, created to identify high-tech solutions that will make the high voltage transmission infrastructure increasingly safe, sustainable and resilient. We are convinced that innovation is one of the main enablers of the energy transition and innovating means interacting with startups to introduce new tools and technologies, which are crucial for the evolution of the electricity sector", he commented Massimiliano Garri, Director of Innovation & Market Solutions at Terna.
Eoliann
In detail, Eoliann is a Turin startup from climatetech, founded in 2022, which uses satellite data and machine learning algorithms to predict the probability, intensity and impact of extreme climate events. Their goal is to improve infrastructure resilience and climate risk management. The partnership between Eoliann and Terna will focus on the use of satellite images and Eoliann models as a source of data to improve the calculation and evaluation of hydraulic hazards: a useful solution for the company in planning new power lines, as well as in the management of existing ones, in areas potentially more exposed to extreme weather phenomena.
Fast Computing
Fast Computing, a Trieste startup founded by the applied mathematics research group of Sissa (International School of Advanced Studies), specializes in statistical models e computing technologies for real-time data analysis. The startup will develop for Terna a model, based on company data, for predictive maintenance of machinery located in the company's electricity stations, in order to estimate the probability of any anomalies and anticipate the need to resort to maintenance operations.
