German companies Kaiserwetter Energy Asset Management and SAP have launched a cloud-based platform to predict wind turbine failures.
The Aristoteles Data Analytics as a Service platform uses predictive analytics and machine learning to turn technical, financial and meteorological data into actionable, real-time intelligence for customers.
Aristoteles can utilise historical technical data from wind turbines to feed continuously learning algorithms that can detect failures in advance.
Kaiserwetter chief executive Hanno Schoklitsch said: “Predicting renewable energy asset failures before they occur is a significant AI achievement in the energy sector – this is a huge advantage for Aristoteles users.
“I’m very proud of the collaborative work between Kaiserwetter and SAP to make this capability a reality.”
SAP head of machine learning Markus Noga said: “As we continue to advance our machine learning capabilities, Kaiserwetter’s customers will benefit from new capabilities and additional functionality.”
The companies are working on extending the predictive feature to other forms of renewable energy generation, including solar, hydro, biogas and biomass.