An exciting area for development that TWI is now focusing on is the harnessing of digital twin technology as the basis for lifecycle engineering asset management.
In recent years, TWI has built up a wealth of knowledge in the structural health and condition monitoring of wind turbines as a result of its participation in a number of significant, European and UK collaborative projects including CMSWind, WTBMonitor and TOWERPOWER. Therefore, it was a natural progression to develop the application of digital twin technology to transform the process of monitoring and maintaining offshore wind turbines.
The digital twin model
The collective body of TWI’s work on wind turbines has sought to address each component of the wind turbine in turn, first determining potential problems that could arise, then subsequently developing new monitoring solutions to mitigate part failure. An offshore wind turbine is composed of a series of parts, typically the nacelle (generator), blades, a foundation structure (piles/buckets, monopile/jacket), a transition piece and a tower. Experience shows that when problems occur they often arise from ageing, resulting in fatigue cracking, loosening of bolts, joint degradation, erosion and other issues.
The application of digital twin will build on the component approach with TWI aiming to deliver a fully integrated solution to structural health monitoring for improved reliability of wind turbines. A condition monitoring system will encompass the entire physical wind turbine providing ongoing structural health analysis. Simultaneously, this will be mirrored virtually with the creation of a 3D model of the wind turbine in the form of a digital twin, including input from different sensors positioned across the physical entity, to continually feedback monitoring data. The output will be fully comprehensive, real-time assessment of the structural condition of individual wind turbine assets.
Benefits of digital twin
Digital twin’s intelligent data processing capabity makes it an ideal platform for preventive and predictive maintenance of the wind turbine’s behaviour and condition. Virtual models, or twins, will combine mathematical models describing the physics of the turbine's operation, with sensor data collected and processed from real assets during real world operations.
Wind farm operators will benefit from being able to predict structural failure and plan maintenance activities with greater accuracy, affording them more control, resulting in reduced maintenance costs and operational downtime during the wind turbine’s lifespan. Overall, this should lead to significant benefits for operators in the wind energy industry world wide.
For more information, please email firstname.lastname@example.org. You can also find out more from our article on lifecycle engineering asset management through digital twin technology.