Unexpected load events measured on operating wind turbines are not accurately predicted by numerical simulations. We introduce the periods of constant wind speed as a possible cause of such events. We measure and characterize their statistics from atmospheric data. Further comparisons to standard modelled data and experimental turbulence data suggest that such events are not intrinsic to small-scale turbulence and are not accurately described by current standard wind models.

This study examines how atmospheric phenomena affect the recovery of wind farm wake – the disturbed air behind turbines. In regions like Oklahoma, where wind farms are often clustered, understanding wake recovery is crucial. We found that wind farms can alter phenomena like low-level jets, which are common in Oklahoma, by deflecting them above the wind farm. As a result, the impact of wakes can be observed up to 1–2 km above ground level.

This paper presents a systematic study of the effect of blade inclination angle, chord distribution, and blade length on vertical-axis wind turbine performance. It shows that, for rotors of identical power production, both blade volume and rotor torque can be significantly reduced through the use of aerodynamically optimised inclined rotor blades. This demonstrates the potential of vertical rotors to reduce the cost of energy for offshore wind when compared to horizontal rotors.

A methodology for evaluating fretting in wind turbine pitch bearing raceways is presented, and a case study is evaluated. The methodology considers the coupled effects of radial fretting and rotational fretting. As result, critical locations based on the dissipated energy are identified for the different wind speeds and the contributions of operational and non-operational times, as well as the prediction of damage shapes on the raceway for both cases, are evaluated independently and compared.

A digital twin is a virtual representation that mirrors the wind turbine's real behavior through simulation models and sensor measurements and can assist in making key decisions such as planning the replacement of parts. These models and measurements are, of course, not perfect and only give an incomplete picture of the real behavior. This study investigates how large the uncertainty of such models and measurements is and to what extent it affects the decision-making process.

Traditionally, the aerodynamic loss of wind farm efficiency is classified into wake loss and farm blockage loss. This study, using high-fidelity simulations, shows that neither of these two losses is well correlated with the overall farm efficiency. We propose new measures called turbine-scale efficiency and farm-scale efficiency to better describe turbine–wake effects and farm–atmosphere interactions. This study suggests the importance of better modelling farm-scale loss in future studies.

This paper adds to the literature on rotor disk theory by solving a century-old problem with a different mathematical approach. The classical results are recovered, while also adding expressions and asymptotic limits for performance coefficients that were not included in the original theory. This work adds to classical rotor disk theory as a valuable contribution to research and teaching in wind turbine aerodynamics.

This paper presents a probabilistic cost model for inspection and maintenance (I&M) of turbine support structures in offshore wind farms. It provides the basis for decision-theoretical optimization of I&M strategies and accounts for uncertainties in the costs. The model can be used to optimize I&M strategies at the component, structural system, and wind farm level. Additionally, a simplified method is provided for I&M optimization for individual turbine support structures.

Our study reveals how different weather patterns influence wind conditions off the US West Coast. We identified key weather patterns affecting wind speeds at potential wind farm sites using advanced machine learning. This research helps improve weather prediction models, making wind energy production more reliable and efficient.