Source: BAM
The Federal Institute for Materials Research and Testing (BAM) will present three innovative developments from its Wind@BAM Competence Center at the Hannover Messe from April 20 to 24. These are intended to make offshore wind farms even more economical and the operation of existing plants safer and more resource-efficient. AI and digitalization play a central role in this.
More efficient and durable foundations
To ensure that offshore wind turbines stand securely in the sea, they require a foundation capable of withstanding waves, storms, and extreme mechanical forces. This is usually a so-called monopile: an enormous steel pipe, sometimes over 100 meters long and up to twelve meters in diameter, which is driven into the seabed.
Their manufacture requires significant amounts of resources: a single monopile can consist of over 2,000 tons of steel. The associated welding processes also require a high energy input. At the same time, these structures are generally designed for a service life of no more than 30 years – a lifespan determined primarily by corrosion and mechanical stresses in the marine environment.
This high resource consumption poses a challenge to the German government’s expansion goals for offshore wind, as it ties up capacity in production and logistics and negatively impacts the economic viability of wind farms.
This is where the OptiMP collaborative project comes in. It examines the entire process chain – from the design of a monopile through its manufacturing, transport at sea, and installation on the seabed, all the way to ongoing operation. The goal is to achieve material savings of up to ten percent and service life extensions of up to 30 percent.
AI-powered rotor blade inspection
The energy output of wind turbines depends heavily on the condition of their rotor blades. Erosion at the leading edge, in particular, reduces efficiency, as damaged areas cause turbulence in the airflow.
In the KI-VISIR project, BAM, together with two startups, has developed a digital, AI-supported inspection method for rotor blades that can be performed during ongoing operation. Thermal imaging cameras capture the surface temperature of the rotor blades from the ground, allowing conclusions to be drawn about the surface condition and internal structures.
The thermographic data is analyzed using artificial intelligence (AI). The method is faster and more informative than many previous approaches, as it detects emerging damage at an early stage. This reduces maintenance costs and increases operational safety. Overall, the annual average output of wind turbines can be increased by up to two percent.
Digital Tool for continued operation and repowering
Many offshore wind farms will reach the end of their planned service life in the coming years. Operators must decide how to proceed. Options include continued operation, repowering (i.e., replacing turbines), or decommissioning a wind farm.
The ReNEW project is developing a digital decision-making tool for this complex situation. It combines technical information and condition-improving measures with economic efficiency. This allows the remaining service life to be utilized to the fullest, enabling operators to make reliable decisions regarding the optimal continued use of their wind farm.
Where to find us
BAM will present its research at the joint booth of the Federal Ministry for Economic Affairs and Energy (BMWE) in Hall 11, Booth B49. For more information on BAM’s presentation, visit www.bam.de/hannovermesse-en.
Press interviews
We cordially invite journalists to visit our booth and speak with us. We would also be happy to arrange an interview with our researchers for you.