We developed a new method to predict when wind turbine parts are likely to fail, allowing maintenance to be planned before costly breakdowns occur. By combining real measurements from turbines with knowledge of how cracks grow in metal, our approach gives more reliable forecasts even when only limited data are available. We also measure how confident the predictions are, helping operators make better decisions. This can reduce downtime and lower the cost of wind energy.

The growing interest in high-velocity physics justifies research into new experimental aerodynamics. Our work provides the knowledge foundations for the next generation of large wind turbine rotors, investigating the FFA-W3-211 airfoil. We highlight airfoil-dependent static and dynamic results from a large-scale wind tunnel experiment. The results delve into the force enhancement due to dynamic oscillations, broken down by Reynolds number and reduced frequency.

This research addresses the need to predict the dynamic behaviour of wind turbine wakes. We developed a new computer model, PhyWakeNet, that combines physical laws with artificial intelligence. This model successfully simulates how a turbine's wake evolves over space and time under oscillating forces on blades. This capability is a significant step forward, as it can lead to better control strategies for entire wind farms, ultimately helping to improve wind farm performance.

A multi-fidelity approach is leveraged to investigate the capabilities of engineering models to capture the wake dynamics of a wind turbine model under imposed motion. In contrast to previous studies, many more different operating conditions have been investigated, including surge, pitch, yaw, and wind–wave misalignment cases; moreover, numerical methods are here consistently applied to the same test cases, which are part of the first experimental round of the NETTUNO project.

This study tested a two-lidar system to measure wind variations more accurately than traditional single-lidar methods. By comparing 30 days of measurements with a reference instrument, we found that the new approach better captures turbulence and reduces errors in both along- and cross-wind directions. The results show that it can provide more reliable ground-based wind measurements, supporting improved weather monitoring and wind energy assessments.

Floating wind turbines are subject to complex aerodynamics that are not yet fully understood. Lab-scale experiments are crucial for capturing these phenomena and validating numerical tools, but due to the different physics, this is difficult with traditional approaches. This paper presents a new, hybrid wind tunnel experimental setup capable of reproducing the coupled aerodynamic and motion response of floating wind turbines.

This study introduces an extended sea surface levelling method for the accurate offshore calibration of scanning lidars. This method can determine the alignment of the laser beam, including any vertical shift, and is independent of the scan pattern. Tests using real measurement data and a detailed uncertainty study confirm its reliability. The study offers a versatile calibration approach and improves confidence in offshore wind measurements with scanning lidars.

Areas with hills and valleys can be either beneficial or challenging for wind energy applications, depending on the wind patterns. Unfortunately, predicting wind patterns in these areas is also challenging, and investing in measurement towers to improve wind forecasts can be expensive. We evaluate ways in which wind farm developers and other stakeholders interested in improving atmospheric forecasts in these areas can do so in a more cost-effective way.

We tested a small model of an energy-generating kite in a wind tunnel to study its aerodynamic behaviour. By comparing measurements to computer simulations, we validated the models and identified where they match the real performance and where they fall short. These insights will guide more accurate aerodynamic modelling and inform design choices for kites used in airborne wind energy systems.

This study explores how the height of the atmosphere's boundary layer impacts wind farm performance, focusing on how this factor influences energy output. By simulating different boundary layer heights and conditions, this research reveals that deeper layers promote better energy recovery. The findings highlight the importance of considering atmospheric conditions when simulating wind farms to maximize energy efficiency, offering valuable insights for the wind energy industry.

Wind farms are being developed in areas prone to tropical cyclones. However, it remains unclear whether turbulence models in current design standards, such as the Mann uniform shear model, are suitable for these conditions. For the first time, the Mann model is assessed in depth using high-frequency measurements from four typhoons. Larger-than-predicted spectral energy is found at small wavenumbers in the outer cyclone and, in some cases, in the crosswind component in the inner cyclone.

The lattice Boltzmann method (LBM) is a new method for very fast and accurate wind farm flow simulations. However, information on this method is scattered, and recent developments are unknown among the wind energy community. This review structures the different aspects of the method and answers common questions about it for wind energy researchers. We find that many of the building blocks for a wind farm simulation tool are present and that the LBM is accurate and efficient.