Data acquired by the European Sentinel-1A/Sentinel-B satellites are combined with a semi-empirical model to enable the easy inclusion of atmospheric offshore wind farm wakes in existing atmospheric model datasets. The model improves the agreement of data from an operational forecast centre with in situ measurements in the German Bight significantly.

We studied how very large wind turbines respond to wind forces by using advanced computer simulations that capture both airflow and how the blades bend and twist. Our results show that including the tower and blade twisting is crucial to predict performance and loads accurately. Compared to standard tools, our method gives a more complete picture of turbine behavior. This helps improve the design and reliability of future large-scale wind turbines.

Models of wind behavior inform offshore wind farm site investment decisions. Here we compare a newly developed model to another, historically used model based on how these models represent winds and turbulence at two North Sea sites. The best model depends on the site. While the older model performs best at the site above a wind farm, the newer model performs best at the site that is at the same altitude as the wind farm. We support using the new model to represent winds at the turbine level.

Floating offshore wind turbines unlock vast wind resources in deep waters, but platform motion makes wind speed hard to measure directly. This study develops an estimation method that infers wind speed from rotor rotation alone, using sliding-mode observer theory. Tested in a high-fidelity simulator and validated in a wave-tank experiment, the proposed method achieves comparable or superior accuracy to the Kalman filter, with simpler tuning, faster computation, and greater robustness.

As part of the Offshore Code Comparison Collaboration 7 (OC7) project, load transfer from global analysis models to local structural designs was examined. Different load-mapping workflows from project participants were compared using a shared reference design and consistent checks. Results show that load-mapping choices, pressure application, and treatment of structural flexibility can influence predicted stresses and fatigue, highlighting key sources of uncertainty and providing guidance for more consistent global‑to‑local assessments.

Numerical models used to analyze wind turbines are based on thousands of input parameters. Each of these parameters has uncertainty, which can impact the predicted loads. This work demonstrates a screening technique to identify which parameters ultimate loads are most sensitive to so that more focus can be given to quantifying the possible range of those parameters, with a focus on a floating offshore wind turbine in design load cases with transient events both in the inflow and operations.

This study experimentally investigates how passing rotor blades affect the aerodynamic load on the tower of a large modern wind turbine. The interaction between the rotor and the tower was analyzed using pressure measurements on the tower. Aerodynamic effects previously seen only in computer simulations could be verified by these measurements. The findings help to improve the understanding of how large wind turbines behave during operation and support better turbine design in the future.

Floating offshore wind turbines experience platform surge motion that alters wake dynamics and generates vortex structures. This study uses large eddy simulations with an actuator disk to analyse these structures under laminar, turbulent and atmospheric boundary layer inflows. Proper orthogonal decomposition reveals peak vortex energy at specific Strouhal numbers, with lower energy and faster decay under atmospheric conditions. Meandering and wake modulation are dependent on inflow conditions.

At night, wind farms can experience a wide range of intermittent wind events that can affect how much power is produced. We modeled a specific type of intermittent wind event that happens as the atmosphere gets colder and colder throughout a night. We identified a threshold to determine when these events impact wind farms and ultimately found that mainly the front of a wind farm tends to be most impacted by these sorts of events.

This study presents a new way to simulate the wind in the lower atmosphere while taking into account the changes in temperature. The model is much faster than previous models while having the same level of accuracy. This study is a step toward making highly accurate software to predict the output of wind farms fast enough for use in the wind industry, ultimately making electricity from wind energy cheaper and more reliable.

Vibrations in wind turbines caused by wake vortices are well known but difficult to predict during design. This study examines a calibrated mathematical model replicating a cantilevered cylinder experiment under vibration-prone conditions. Results show the model’s ability to capture the body’s response while offering greater insight than current state-of-the-art prediction tools.

When wind turbines operate in conditions which they were not designed for, e.g., complex terrain, they might show unexpected performance variations. Complex-terrain flow physics, such as streamwise flow acceleration, alter maximum performance. It is asked whether this also affects steady-state turbine control. We show that rotor-torque-based control strategies can lead to suboptimal control in these conditions, but the effect of the background flow on performance is larger.

This study explores improvements to an atmospheric measurement method called acoustic tomography, which uses sound travel times to estimate wind and temperature. We compare several ways of estimating how air conditions vary and show that models based on realistic wind turbine simulations yield more accurate results than traditional simplified methods. These findings support better observations of complex air flows around wind turbines, helping advance renewable energy research.

Wind turbine interaction can lead to energy losses. This article introduces a fast open-source wind turbine interaction model that can be used to design energy-efficient wind farms, including effects of atmospheric turbulence and temperature. The model can inherit the accuracy of a higher-fidelity model while being about 5 orders of magnitude faster. However, the model is an order of magnitude slower than analytic wind turbine interaction models, and more research is needed to reduce it.

Wind energy is key to the energy transition. Airborne wind energy (AWE) is a technology based on kites. It has many advantages. However, their operation in gusts or in farm configurations remains unexplored. This work proposes a tool for studying AWE systems in such conditions. It is used to investigate a two-kite array. It is found that the second kite can avoid the wake of the first kite and stay unperturbed, while in other situations it produces 6 % less energy.

Numerical simulations of 35 different combinations of terrain, wind farm layout, and atmospheric conditions indicate that terrain (i.e., ground elevation variation) can significantly influence wind farm flows and in turn energy extraction efficiency. An analysis of the simulation results identifies the main drivers behind these terrain effects. These influences should be accounted for when estimating the energy yield of a planned wind farm – at least for wind farms similar to those in this study.

Wind farms extract energy from the wind, creating slower, more turbulent flows that can affect other farms downstream. Using high-fidelity simulations for comparison, we find that mesoscale simulations that parameterize wind farms at coarser resolution may underestimate how quickly the wind recovers downstream. This slow recovery results from missing sharp wind gradients and low turbulence. Improving these aspects can help better predict wind energy production over long distances.