Optimal Operational Planning of Wind Turbine Fatigue Progression Under Stochastic Wind Uncertainty

Wind turbines are designed to operate continuously over a lifetime of at least 20 years. During this time, they are prone to high loads under various site-specific environmental conditions. All large structural components like e.g., the tower and the rotor blades are designed to withstand the loads over their entire lifetime under consideration of the environmental conditions. The requirements for operation are safeguarded by national and international standards and uncertainties are often compensated by conservative assumptions and partial safety factors. One of the main design drivers for the structural components is fatigue damage (Liao, Ding et al., 2022). The crack growth is induced by cyclic forces and bending moments at various places of a turbine and are thus influenced not only from the environmental conditions but also by the operation of a turbine. Intelligent operational management can be used to make best use of the available load bearing capacity.
We developed a method which creates an optimal long-term operational planning by optimally distributing the damage contribution over the entire or remaining lifetime (Requate et al. 2022). The planning makes use of the nonlinear relationship between external conditions, load reducing control and induced fatigue damage. Currently, this optimization is based on deterministic assumptions where an individual target damage needs to be specified for each component. Now, we use uncertainties of annual wind distribution parameters as the basis for a probabilistic assessment of time to failure for each component. This allows for combination using a simple reliability model, which yields the lifetime of the entire wind turbine system. The impact of individual component optimizations on overall system reliability is evaluated. Results show that all approaches yield a potential for extended lifetime, however the margin and the secondary impact differ greatly. Simultaneously, the span of probabilistic lifetimes emphasizes that uncertainty has a significant impact on the selection of an optimal strategy. Our findings provide a step towards a probabilistic and reliability-based long-term operational planning for an entire wind turbine system that is composed of multiple components.