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Analytics for asset Integrity Management of Windfarms (AIMWind)

Analytics for asset Integrity Management of Windfarms (AIMWind)

, Photo: Nicholas Doherty through Unsplach.com, Nicholas doherty p ON Bh Dy O Fo M unsplash, ,

Photo: Nicholas Doherty through Unsplach.com

About 65 GW of onshore wind turbine installations in Europe will reach end-of-design-life by 2028. It is time for the operators to decide on one of the three end-of-life scenarios, namely, decommissioning, lifetime extension, or repowering. The last two options will increase the operating life and thus reduce lifecycle costs. These end-of-life decisions require careful consideration of the accumulated fatigue life of each turbine in a wind farm to minimize monetary risk for the wind farm operators. Today, this decision is primarily based on a single point assessment by the certification authority.

AIMWind proposes a continuous evaluation of wind farm health based on big data analytics using multimodal data such as wind, operational data, weather, condition monitoring, and inspection logs across a wind farm. Conventional approaches to fatigue estimation are slow and inadequate to achieve these goals, especially in large wind farms. Such a continuous health assessment will facilitate not only accurate life predictions but also continuous improvement of wind turbine operations to ensure long life and high availability.

Project facts


Analytics for asset Integrity Management of Windfarms (AIMWind)




01.01.21 - 29.12.23



Research group

Research Topics


Research Council of Norway (RCN)


Universitetet i Agder

Project members

Kjell Gunnar Robbersmyr
Christian Walter Peter Omlin
van Khang Huynh


Universitetet i Agder, NORCE
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