This research explores a method for repairing wind turbine blades made from carbon fiber while they remain installed, eliminating costly disassembly. It addresses the challenges of repairing damaged blades and proposes a practical solution to improve repair efficiency. Through structural analysis, we found that this approach can ensure safety during repairs, providing significant benefits to the wind energy industry.

This study presents a new wind dataset, generated by a convection-permitting regional climate model across North America. By validating the dataset against wind observations, we have demonstrated that this dataset captures the wind patterns over complex terrains more realistically than the European Centre for
Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5). Additionally, this study quantifies model uncertainty in wind speed, comparing it against interannual variability, to better inform wind farm siting. 

Tilting wind turbines change the airflow behind them, which can lower energy production in wind farms. This research tested both a traditional physics-based model and a deep learning method to predict these effects. While the traditional model improved with added optimization, it struggled with complex wake patterns. The deep learning approach was faster and more accurate, showing potential for better wind farm design and control with reduced computational cost.

Offshore wind turbines can be directly impacted by the jet maximum winds of low-level jets, which makes them very important to the wind energy community. Here, we simulate an offshore low-level jet event using a weather model from low resolution to very high resolution. We run the simulations several times, varying the sea surface temperature to generate different realizations of the event and comparing against observations. We then ask and answer: "Is model performance consistent across scales?"

This study analyzes onshore wind farm wakes in a semi-complex terrain with data conducted with the research aircraft of TU Braunschweig during the American WAKE experimeNt (AWAKEN). Vertical profiles of temperature, humidity, and wind give insights into the stratification of the atmospheric boundary layer, while horizontal profiles downwind of wind farms reveal an amplification of the reduction in wind speed in a semi-complex terrain, in particular at a distance of 10 km.

Hollow forging and air-hardening ductile steel enable higher power densities for wind turbine main bearing units. For a 2.3 MW base-load-optimised wind turbine, a 37 % increase in rotor shaft power density was achieved compared to a casted shaft. By using green, air-hardening steel, hollow forging achieves a comparable global warming potential to casting. The economic viability of hollow forging is not given for the current surcharges found in small-series production.

Various simulation tools exist to provide load forecasts in the wind energy field (engineering models and numerical simulations). A newly introduced concept is the center of wind pressure, a quantity extracted from a wind field. In previous works, similar behaviour, then the main shaft bending moments, was shown. However, a clear relationship is missing. In this work, this gap is filled through the introduction of a calibration parameter.

A new model incorporates vortex generator (VG) effects into fast aerodynamic tools like XFOIL and RFOIL. It modifies boundary layer equations and uses empirical functions scaled with VG geometry and Reynolds numbers to implement the modified integral boundary layer equations in RFOIL. The model improves accuracy across airfoils and predicts separation delay, stall delay, lift increase, and added drag, enabling VG effects to be included in wind turbine blade design.

Mountain waves can form when air passes over a large barrier and can cause strong winds on the lee side. Understanding how these strong downslope winds impact wind power production can help improve wind park efficiency. We studied two wind parks in Norway and found that the turbines on the leeward side of the mountain produce more power than the turbines on the mountain top. This study also investigates how weather models can help predict when and where strong downslope winds may occur.

Neighbouring wind turbines influence each other, as they leave a complex footprint of reduced wind speed and changed turbulence in the flow, called wake. Modern wind farm control sees the turbines as team players and aims to mitigate the negative effects of such interaction. To do so, the exact flow situation in the wind farm must be known. We show how to use wind turbines as sensors for waked inflow, test this in the field and compare it with independent laser measurements of the flow field.

This paper investigates the optimal aerodynamic design of the wing and the onboard turbines of the fly-gen airborne wind energy system aircraft, named wind plane here, with a novel comprehensive engineering aerodynamic model and with the vortex particle method. Placing the turbines at the wing tips, rotating them inboard downward with a low tip speed ratio, and using conventional efficient airfoils for the wing are found to be optimal for wind planes.

How much hourly wind data are enough for reliable resource assessment? Using long-term station records and reconstructed datasets, we test sample sizes and sampling strategies. Means, variability, and Weibull scale converge within a sample size of 1 month of hours, but distribution shape needs far more. Random cross-year sampling reaches a given accuracy with far less data than continuous sampling.

This work extends a model of wind farm interaction with the atmosphere to account for Coriolis forcing. The model now embodies many aspects of atmospheric dynamics in a manner that remains fairly simple and is very quick to run. The motivation is to investigate the conditions under which Coriolis contributes significantly to wind farm wake recovery. The model results and associated analytic expressions provide these insights, which can be important when modelling offshore wind wake loss.

Most important for finite-element models is validation to ensure reliable results. To the knowledge of the authors, all publicly available large rolling bearing models are not validated. This work introduces a finite-element model of a 5 m roller bearing as a wind turbine blade bearing. The authors investigated the influence of different bolt preloads on the bearing rings and validated the model against experimental data using a large blade bearing test rig.

We verify wake effects between two wind turbines in complex terrain using supervisory control and data acquisition data. By identifying “wake conditions” and “no-wake conditions” detected by the blade pitch angle of upstream wind turbines, we evaluate wake effects on wind speed ratio, turbulent intensity, and power output. Results show that flow downhill has a significant impact on wake effects compared to flow uphill. The method shows the potential of SCADA data during the downtime of wind turbines.

Airborne wind energy systems (AWESs) are an emerging technology for power generation using tethered aircraft. The flight dynamics characteristics of rigid-wing AWESs in circular flight is discussed. We examine the cyclic control input to achieve circular soaring flight while being tethered. It was also found that large-radius circular orbits are unstable. The insights gained from this research can help to inform future control design for rigid-wing AWES.

This study, a part of the Blade Extensions for Silent Turbines project, explores how turbulent airflows affect the noise generated by large onshore wind turbines. Using advanced simulations and an analytical model, we show that as turbine blades grow larger and thicker, turbulence behaves differently near the blade, changing how noise scales. These insights help to design quieter, more efficient next-generation wind turbines.