Case study

Developing an aeroelastic digital twin to understand asset performance

We supported the development of a process that facilitated a load match between that observed in real-life with simulation results.

Overview

Our customer, a wind farm developer, was looking to understand more about their asset’s performance, and to improve confidence that its turbines were operating as expected. This formed part of a wider interest in mapping data to site specific models to provide increased certainty around energy production and fatigue loads.

Our work

We worked closely with our customer to build up a turbine aeroelastic model in FAST (fatigue, aerodynamics, structures, and turbulence) and developed appropriate design activities to facilitate a match between actual turbine performance and simulation.

Our work included:

  • Asset modelling – Understanding what parameters of the model needed upscaling to match key load sensors of the turbine e.g., blade, hub inertia or tower height.
  • Control system design – Developing a controller to ensure that the operating points of the system are matched, such that appropriate loading decisions can be taken.
  • Power performance analysis – Developing a process to map a power curve with data/simulation to create a load profile that informs life extension decisions for the asset.
  • Load analysis – Understanding blade extreme and fatigue loads as well as tower loads, to inform lifting decisions of the turbine.

 

Impact

The key output of this work was the development of a process that facilitated a load match between that observed in real-life with simulation results. Our implicit understanding of the physical model and the underlying control implementation was pivotal in providing this match. With appropriate refinement, this approach will inform operational decisions around life extension and maintenance strategies.

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