Our wind turbines are getting old—or at least on paper. 

Some have been in operation for more than 20 years, and the oldest turbines in Denmark are nearing their nominal end-of-life. 

“The lifetime is based on a conservative estimate. In reality, they may be able to operate for 30 years, so many still have good years ahead,” says Frederik Nordtorp.

He is a Ph.D. student at the Department of Civil Engineering and Building Design, researching whether more precise testing can extend turbine lifetimes—benefiting both the economy and the climate. 

“Imagine if they could remain in operation for another ten years. It would require refurbishment of specific components, but it would prevent the turbines from being decommissioned prematurely,” he explains.

Current Methods and Their Limitations

Today, turbine lifetime is typically evaluated through operational data analysis and physical inspections.

These methods provide only a limited picture of the actual condition of the most stressed components. There is therefore a need for a more precise approach. 

Hybrid testing is one such solution. 

It combines physical testing of turbine components with a digital model simulating the rest of the turbine.

“It’s really like trying to fit a Lego brick into a jigsaw puzzle,” explains Nordtorp. 

Challenges arise when the physical and digital tests need to interact accurately. The young researcher, however, appears to have found a solution.

Currently, various testing methods are in use. Some in the industry rely on physical tests to evaluate how a turbine component performs under specific conditions. 

Others use computational models to simulate turbine behavior. 

“Both approaches have significant advantages, but also substantial limitations,” says Nordtorp. 

Physical tests capture only local effects, while simulations do not always represent all details of real-world loading.

“It is a challenge for the industry that the two tests don’t communicate. We are missing a lot of valuable information about turbine behavior,” he explains.

Hybrid testing combines both approaches. 

A physical component—such as a pitch bearing, a large ball bearing that adjusts the blade’s angle to the wind—is tested while its interaction with the rest of the turbine is digitally simulated under realistic loads. 

This allows engineers to assess the bearing’s condition and how its fatigue affects the turbine as a whole. 

“This gives us a very accurate picture of how worn a critical component is—and when and how it should be refurbished,” Nordtorp explains. 

When the tested turbine operates alongside others, the results are representative for the fleet.

One challenge remains: the interaction between the physical component and the digital model can be unstable. Even small errors or delays can cause unrealistic behavior. 

“We are researching how to make hybrid testing more robust and stable—and there is strong evidence that it is possible,” says Nordtorp.

Potential Applications Beyond Wind

Nordtorp has developed a method to stabilize the hybrid test in real-time, even under delays or complex motions. 

“Essentially, we try to predict what will happen and program accordingly,” he explains. 

This predictive approach synchronizes forces and motions between the physical and digital components, ensuring realistic system behavior even under complex, nonlinear dynamics. 

“The method provides a reliable solution, allowing components to be tested under realistic conditions without interaction instability,” says Nordtorp.

Hybrid testing is not limited to wind turbines. Any system with complex, varying dynamics can benefit, including cranes, spacecraft, and other large mechanical systems.

In the context of renewable energy, hybrid testing could be key to extending the operational life of offshore wind turbines. 

“It would be wasteful to decommission turbines unnecessarily. We need precise and reliable testing methods to confirm that turbines can continue operating safely for many more years,” Nordtorp says. “We now have that. Hybrid testing can save both time and money while improving safety.”

Frederik Nordtorp is supervised by Professor Giuseppe Abbiati and will submit his Ph.D. thesis this summer.