In summary, this study develops and validates an advanced beam element formulation that successfully addresses two critical challenges in structural analysis: accurate modeling of variable cross-sections and robust simulation of geometric nonlinearity. The comprehensive validation framework demonstrates the method's reliability across multiple benchmark cases, establishing its potential for engineering applications requiring precise analysis of tapered beam structures under large deformations.

Turbulence over the ocean at heights relevant to modern offshore wind turbines, i.e., up to 300 m or more, is not well studied. It is important to know the properties of this turbulence because it is responsible for most of the dynamic loads on these structures, and consequently it is relevant to how the latter should be designed. This data description paper explains the efforts made to provide measurements of this offshore turbulence using five Doppler lidars.

Wind farms suffer power losses and increased structural loading due to wake interactions. The helix method mitigates this by continuously moving upstream turbine blades to accelerate wake recovery. We developed two surrogate models from high-fidelity simulations: one identifying optimal pitch settings, achieving 7.5 % power gain, and one predicting fatigue loads under various conditions. This enables joint evaluation of power gains and load penalties, supporting informed wind farm control design.

This study addresses the challenges of applying aerodynamic loads to a multibody reduced-order model based on solid finite elements. This model differs from the beam models typically used in wind turbine aeroelastic simulations by relying on a higher-fidelity finite element model. The results show that the proposed load application methodology produces accurate structural responses, while also identifying best practices for this process.

This work presents an investigation into varying modelling choices for large-eddy simulation over realistic forests. The focus is on how to represent the impact of upstream forest cover on wind statistics. The work clearly demonstrates the advantage of using an explicit drag formulation together with forest density maps from airborne laser scans over using roughness length and displacement height, mainly because it leverages observable quantities and minimizes the impact uncertain choices.

This work presents the outcomes of an acoustic experimental campaign conducted on an industrial wind turbine under normal operation and yaw misalignment. The objective of this test was to study the effect of yaw misalignment on turbine noise magnitude and directivity. The results show a slight increase in the noise emitted by the turbine when it is misaligned and a rotation of the noise directivity pattern consistent with the rotation of the nacelle.

This study examines how a newly built offshore wind farm affects the power production of nearby existing wind farms. Using a full year of simulations, we compare detailed weather-based models with faster simplified models. The results show clear differences in predicted power losses, especially during calm summer conditions, highlighting the importance of model choice for future offshore wind farm planning and design.

This study examines how a newly built offshore wind farm affects the power production of nearby existing wind farms. Using a full year of simulations, we compare detailed weather-based models with faster simplified models. The results show clear differences in predicted power losses, especially during calm summer conditions, highlighting the importance of model choice for future offshore wind farm planning and design.

Large offshore wind turbines are exposed to slow changes in wind speed, which are often overlooked in design studies. We investigate how these slow wind variations impact the forces and motions of both fixed and floating wind turbines through computer simulations. Slow wind changes can lead to increased long-term structural wear and significantly impact platform motion in floating turbines. Accounting for these variations is crucial for the design and lifetime assessment of future turbines.

We present a detailed experimental investigation of the flow details of the blade/tower interaction (BTI) on a 1.5 MW wind turbine operating in a downwind configuration. The objective is to clarify some of the most important barriers for the downwind turbine concept linked to the impulsive loading from the blade/tower interaction generating low-frequency noise and increased loading. Unique instrumentation was used, comprising two extruded pressure belts on one of the blades and on the tower.

Load monitoring for wind turbine support structures is essential as turbines approach the end of their design life. Typically, load monitoring involves estimating strain from vibrational measurements. This paper introduces an approach that uses a biaxial and DC-capable acceleration sensor to estimate strains across all fatigue-relevant excitation frequencies on the entire support structure, enabled by compensating for gravity-induced biases in acceleration measurements.

This study introduces a method for detecting wind turbine blade erosion by approximating the outputs from aerodynamic simulations with a Gaussian process emulator. Once trained, querying the emulator is essentially free, which enables the efficient generation of datasets for training damage classification models. This framework could provide an essential building block for constructing a digital twin for wind turbine condition monitoring.

This work investigated the effect of a variety of floating-wind-turbine motions on the wake, the slower and more turbulent air left behind the rotor. This was done via computational simulations that reproduced a wind tunnel setup to test the tunnel's impact. While some motions barely disturbed the wake, other motions produced a remarkably different wake structure. The wind tunnel walls influenced the wake to some degree, but the general behavior was consistent with what is seen in the open air.

This study explores how grease moves inside large rotating components used in wind turbines. Using advanced computer simulations, we modeled the real-life behavior of grease under the influence of gravity and motion. Our findings show that the tilt and size of the component greatly affect how grease spreads and performs. This helps improve the design and reliability of wind turbines for long-term, efficient energy production.

Floating wind turbines can become unstable when controlled like land-based turbines, due to motion at sea, which causes oscillations that increase damage and affect power output. This research revisits existing control strategies and introduces a controller that improves stability using only the standard speed sensor, without extra equipment. Time-domain simulations show that it matches or outperforms existing methods in reducing structural loading, highlighting the need for tailored offshore controls.

This study examines the risk drivers of the economic success of wind energy projects and how interacting risks threaten that success. We combined expert opinions, survey results, and literature findings to identify key challenges in planning and operation. The results show that risks interact and can cause uneven financial losses, highlighting the need for integrated decision support tools.

This research developed an optimal design model for hydrogen and battery equipment for a wind farm in northwest Germany. By accounting for equipment aging and part-load efficiency of a polymer electrolyte membrane electrolyzer, the tool provides a realistic economic assessment. Results show that neglecting these effects leads to a significant overestimation of profits. This method offers developers a reliable way to plan renewable hydrogen systems and ensures secure investment decisions.

We built a small wind turbine model and tested it in a wind tunnel while improving computer simulations. Results show simulations accurately predict wind turbine wake behavior behind spinning blades, matching measurements. Some differences remain near blade roots. Combining experiments with refined models helps engineers predict wind turbine performance with greater confidence, supporting more efficient renewable energy design.

In this study, we use advanced weather simulations, real-world measurements, and satellite images, showing that modeling wind farm effects improves accuracy, especially in areas influenced by turbines. Focusing on one of the largest wind farm clusters in the North Sea, we investigate wind speed deficits based on different atmospheric conditions. These findings help quantify the influence of large wind farm clusters, improve predictions, and support planning for future wind energy development.

A combined dataset of sonic and cup anemometer measurements, together with synchronized short-range lidar observations, is used to derive turbulence characteristics, including integral length scales, auto-spectra, and spatial coherence. The instruments exhibit strong agreement and consistent trends across atmospheric stability. Deviations at high frequencies are attributed to spatial averaging effects. Empirical models fitted to the data closely reproduce the spectral estimates.