Wind Farm lifetime extension and remaining useful life calculation

RUL - imagen_english
Cases And Applications

LTE and RUL calculation

SCOPE
  • Is it possible to extend the service life of wind turbines beyond their original design life?
  • Which components present the highest risk of failure?
  • Which O&M strategies can help reduce risks and maximize profitability?

Wind turbine lifetime extension has become a key strategy for maximizing asset profitability once the original design life has been reached.

In this context, Aeroblade developed a Remaining Useful Life (RUL) assessment aimed at evaluating the structural and operational condition of the wind turbines within a wind farm that had been in operation for 15 years. The study enabled the identification of potential risks and the definition of tailored operation and maintenance strategies to support the safe extension of the assets’ operational life.

The assessment combined aeroelastic modelling, site characterization, and advanced structural evaluation methodologies to analyse asset performance and determine their remaining operating potential.

The study scope included:

  • Creation of a digital twin of the wind turbine platform under evaluation.
  • Characterization of the site’s specific environmental and operating conditions.
  • Remaining life calculations for the main turbine components.
  • Identification of life-limiting and critical components.
  • Definition of technical recommendations and tailored lifetime extension strategies.
LTM2
Customer benefits

The assessment provided valuable insights into the condition and performance of the assets, supporting informed decision-making and reducing uncertainty associated with long-term operation beyond the original design life.

The main benefits achieved included:

  • Data-driven risk assessment based on real operating conditions.
  • Identification of life-limiting and critical components.
  • Optimization of operation and maintenance (O&M) strategies.
  • Technical support for risk evaluation and asset management decisions.
  • Informed decision-making supported by robust engineering analysis.