“Wind Big Data Boost involved more than 4,000 wind turbines from the global EGP fleet, including all the machines in Italy and Spain.”
Thanks to artificial intelligence software and machine learning, at work across all the Italian wind farms, we are testing systems that analyse data and identify potential failures at a very early stage.
“Predictive maintenance has allowed us to achieve significant savings and to increase efficiency and availability for all the plants.”
Listening to the heart of our turbines
Every doctor, in order to carry out a diagnosis, needs to have the best instruments available.
In the same way, we’ve chosen one of our Sicilian turbines as a test site for the development of new innovative sensors, able to monitor the operation of the wind turbine from the inside and provide a complete overview of the situation immediately.
“The new Micro Electro Mechanical Systems (MEMS) sensors, built with micro-fabrication techniques, offer optimal performance together with low production costs.”
The MEMS are part of a complete monitoring system able to detect vibrations inside the nacelle and any irregular tower movements.
With very sensitive microphones, the system is also able to “listen” to the blades and internal components of the turbine and detect any operating errors.
At two of our wind farms in Calabria and Sardinia, we are also testing new generations of control devices able to increase performance and reduce structural loads on the whole turbine.
“With new innovative anemometers, the instruments used to measure wind speed and direction, we can improve the control of the wind turbine, favouring efficiency and an increased service life.”
Algorithms that improve plants
Every single turbine is part of a greater wind field, often with hundreds of turbines working together. This is why we consider our plants powered by wind energy as a single body, studying the best technological solutions to optimise their work.
Our Sedini wind farm, in Sardinia, for example, will be the testing site for Closed Loop Wind Farm Control (CL-Windcon), an ambitious project financed by the European Community as part of the Horizon 2020 programme, with the goal of creating advanced control algorithms to improve the functioning of plants as a whole.
“Working with international partners like Milan Polytechnic, thanks to CL-Windcon we are learning to modify the functioning of single turbines based on aerodynamic trails produced by nearby blades and on parameters of the entire plant.”
Following initial high-resolution fluodynamic simulations, the project is now in its second stage, which involves tests with turbines in a wind tunnel. Once this phase is over, CL-Windcon will arrive in Sardinia, where there will be a full-scale test.
Planning for the unpredictable
The wind, as we all know, cannot be activated with a simple remote control. Despite its unpredictable nature, however, wind energy can be integrated with other renewables, in order to make it more “plannable”.
“Using artificial intelligence tools and the most complex systems of weather forecasting, we can predict how much energy a wind farm will be able to contribute to the grid ahead of time.”
Thanks to modern storage systems it’s also possible to store energy, stabilise its frequency and balance supply and demand.
The cost of storage systems is going down rapidly and it is expected that they will spread very quickly in the coming years.
“In Potenza Pietragalla (Basilicata), we are testing an energy storage system integrated with a wind farm to verify the dynamics and challenges of this type of plant in the field.”
Made up of 9 wind turbines for an installed capacity of 18 MW, Pietragalla is a small-to-medium plant, enough to test our capacity in industrial-level storage systems.
The effort we’re making in Basilicata is a key step for the future, as it allows us to gain know-how in an innovative technology that has great market prospects: an experience that will be able to spread from Italy to the rest of the world.
 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 727477. http://www.clwindcon.eu/