The system was proven effective through a series of pilot tests undertaken at BKW's wind farms in France, Germany, Italy, and Switzerland. “In 2020, the algorithms enabled us to identify potential anomalies across our wind turbine fleet. With the help of our responsive field technicians, we were able to prevent machinery failures and turbine shutdowns, which might have caused significant financial losses,” says Arthur Chevalier, Technical and Commercial Manager at BKW Wind Service GmbH.
The innovative solution consists of two components: first, an AI algorithm creates a digital twin of the wind turbine, which continuously provides its expected signal values under the actual operating conditions.
Secondly, another algorithm compares these values with the real-time signal readings from the wind turbine in the field and flags any suspicious discrepancies. It also suggests possible diagnostics to link those discrepancies to the most probable underlying problems.
The solution is available on the market for wind farm operators.
“We have integrated the predictive algorithms in Wind-Log, our digital platform for the asset management of wind farms. Our customers benefit from the predictive recommendations to increase availability and energy production of their assets”
says Giuseppe Madia, Managing Director of Proxima Solution GmbH.
