Fatigue crack growth has been observed as a prominent damage mode in rain erosion of wind turbine blades, where it is driven by cyclic pulse loading from liquid droplet impacts. This study investigates fatigue crack growth in a thermoplastic polyurethane elastomer used for leading-edge protection, linking repeated droplet impacts to controlled cyclic loading in a lab test. The plane strain tensile double-slit test method is employed to determine the actual tearing energy during fatigue crack growth. A new analysis technique evaluates tearing energy throughout the test by tracking strain energy evolution with crack length. A novel test fixture with circular grip faces was developed to ensure efficient gripping of polymer sheets. It is examined how the interval between successive load pulses, the dwell time, affects fatigue crack growth per cycle, denoted as
The accurate estimation of hub-height wind speed is crucial for wind resource assessment at prospective sites. Traditionally, long-term wind speed series are derived from short-term site observations combined with reanalysis products, most commonly the ERA5 single-level data at 10 and 100 mm
This study investigates how distributed wind energy could be strategically deployed in areas with elevated energy burdens by analyzing spatial, economic, and demographic factors. We use a set of metrics that incorporate residential and macroeconomic variables to better capture affordability across different income levels. These metrics are correlated with demand-adjusted annual energy production, which reflects DW potential across residential, commercial, and industrial sectors. Using mixed-effect modeling and state-level fixed-effect regressions, we identify key covariates associated with high energy burden. Our results reveal significant geographic variability both across and within states, with stronger correlations between DW potential and residential energy burden in regions where it is closely tied to poverty rates and agricultural activities. While noting that these associations do not imply causal effects, we group states based on correlation strength and DW potential. This highlights potential opportunities to improve energy affordability through targeted siting of distributed wind projects whose low relative cost, ability to be sized to match demand, and potential to create local employment may be leveraged to alleviate energy burdens and drive local economic gains.
This letter clarifies the key parameters governing the wake recovery of a floating wind turbine undergoing surge motions. A dedicated wind tunnel campaign covering reduced frequencies (Stp) well beyond the current literature is presented. This enabled a full characterisation of the wake recovery and the discovery of a previously unreported wake mixing phenomenon. We highlight three main findings: (i) enhanced wake recovery of the surging turbine is highly sensitive to thrust, (ii) wake recovery is characterised by the ratio of motion velocity amplitude to wind speed and Stp, and (iii) a previously unreported flow phenomenon improves wake recovery when the motion frequency is slightly lower than the blade passing frequency.
A theoretical limit for the energy extraction of offshore wind farms has been suggested by Simão Ferreira et al.2026)Simão Ferreira et al.2026)Simão Ferreira et al.2026)Simão Ferreira et al.2026)
In this study, we investigate the impact of vertical wind shear and wind speed inversions on the power production of a floating offshore wind turbine. Using nacelle-mounted wind lidar data from a 6 MW turbine at the Hywind Scotland wind farm, we analyse inflow conditions and turbine performance during summer and autumn. The wind climatology shows that 33 % of examined cases exhibit non-standard wind profiles within the rotor-swept area, including negative shear and wind speed inversions. These conditions can significantly affect power production. In particular, in the below-rated wind speed range, we find differences ranging from 5 % to 10 % between wind profile cases with negative and positive shear. Our findings demonstrate that deviations from the logarithmic wind profile at the operating height range of modern offshore wind turbines can introduce substantial bias in a power curve verification procedure, with differences up to 20 % compared to a reference power curve of a fixed-bottom wind turbine. Nacelle-mounted wind lidars provide critical insight into the inflow offshore characteristics, enabling improved performance assessment of floating offshore wind turbines. The results highlight the need for an implementation of measurement strategies that capture wind conditions across the full rotor-swept area.
A structural and economic optimization framework applicable to floating semi-submersible platforms, demonstrated here for a 15 MW offshore wind design, is presented. A genetic algorithm was developed that can seek a multi-objective solution to minimize mass whilst respecting the constraints of loads acting upon the system. Statistical and machine learning methods are then employed to forecast short- and long-term costs of the platform under a range of exogenous data scenarios, selected to support and boost forecasting accuracy alongside a hybrid forecasting method. Steel mass was reduced from 3916 to 3273 t whilst respecting platform response constraints. The uncertainty in steel prices has the most significant impact on CAPEX, approximately EUR 150–200 million at the 1 GW level. Levelized cost of energy (LCoE) is calculated to gauge the technical and economic viability, with EUR 3–5 MW h−1
Despite many recent advances, modeling wind turbine wakes using semi-empirical and analytical models still faces challenges when dealing with more complicated situations involving wind shear, veer, atmospheric stratification, and wake superposition. To address these limitations, this study introduces a three-dimensional, parabolic Reynolds-averaged Navier–Stokes (RANS) k−ϵ formulation which includes an atmospheric boundary layer model and an actuator disk model for turbine wakes. The full three-dimensional solution for the velocity, temperature, and turbulence variables is efficiently solved through an alternating-direction implicit scheme that requires orders of magnitude fewer computational resources than traditional high-fidelity approaches, such as fully elliptic RANS or large-eddy simulations (LESs). The results of the parabolic RANS model are compared to the equivalent LES and semi-empirical wake models at different wind speeds under stable atmospheric conditions with veer and shear at a single TI level, as well as a convectively unstable-inflow case. For the single-turbine wake the RANS model was able to capture the wake deficit behavior, including the wake stretching and skewing that was observed in the LES. The distribution of the wake turbulence in the RANS model also agreed with results from the higher-fidelity simulations. In simulations of a two-turbine, directly waked configuration, the new RANS model was able to handle the wake superposition behavior without difficulty and also correctly modeled the corresponding increase in wake turbulence when compared to LES. A demonstration of the RANS model on a nine-turbine, three-row wind farm is shown and compared to LES, and comparisons with a semi-empirical veered Gaussian model are also discussed. The work in this study can be generalized in future investigations to handle additional wind conditions and more complex wind farm configurations.
Atmospheric boundary layer flow during stably stratified conditions often exhibits wind veering – the change in wind direction with height – which significantly influences wind turbine wake dynamics and its downstream recovery. This study investigates the impact of veered inflows on turbine wakes through wind tunnel experiments using high-resolution stereoscopic particle image velocimetry (SPIV). A porous disc of uniform porosity is employed as a surrogate for wind turbines to systematically examine wake characteristics under both non-yawed and yawed conditions. The results reveal that veered inflow induces an ellipsoidal-shaped wake for a non-yawed porous disc. Under yawed conditions, however, the interaction between yaw and veer leads to a complex wake shape, where the curled shape due to yaw is superimposed on the wake stretching due to veer. Furthermore, the strength of the two counter-rotating vortex pairs formed around yawed discs is reduced due to wind veering. A budget analysis of the streamwise momentum equation and turbulent kinetic energy is performed to shed light on the mechanism of wake recovery and energy redistribution. The results demonstrate that wind veering leads to faster wake recovery and more available power for downstream wind turbines. These findings imply that, under conditions of extreme wind veer, yawing the turbine may offer limited additional energy recovery, as wind veering alone facilitates significant wake re-energization.
To extend the lifetime of an offshore wind turbine, a lifetime reassessment is required to determine the potential remaining lifetime. This means that the lifetime is recalculated using the combinations of environmental parameters (wind and wave effects) that have actually occurred during the lifetime and which typically differ from the assumed conditions during design. The computational effort of such a lifetime reassessment is significant, as a very large number of aeroelastic simulations have to be carried out. Therefore, according to the state of the art, the number of considered combinations of environmental parameters is reduced similar to the design procedure. In this work, an alternative approach for the lifetime reassessment is investigated in detail. This retains the full set of combinations of environmental parameters while considering both normal operation and idling. The challenge of the high computational effort is resolved by using Kriging meta-models instead of aeroelastic simulations. The meta-model-based approach is compared to two other methods for lifetime reassessment: first, the reference method, i.e. a full lifetime reassessment using aeroelastic simulations where all combinations of environmental parameters which have actually occurred are considered, and second, the approach according to IEC 61400-3. The three methods are compared with regard to the accuracy of their overall lifetime predictions and the computational effort required to make the lifetime predictions. The results show that both the IEC approach and the meta-model approach can achieve good lifetime prediction accuracy compared with the reference method. However, compared to the reference solution, whilst the IEC-based approach can reduce the computational effort to approximately 20 % of the reference solution's computational effort, the use of meta-models can significantly reduce it to less than 0.5 % of the reference solution's computational effort. The results therefore show that, by using meta-models instead of the original aeroelastic simulation model to reassess the lifetime, the computational effort can be significantly reduced compared to the other two methods, while maintaining a high approximation quality in the prediction of the lifetime fatigue loads.
We revisit the modeling, using actuator line methods (ALM), of flow curvature effects on airfoils and their application to vertical-axis turbines (VAT), which is important when the ratio of airfoil chord cR
The rapid expansion of wind farm installations in the North Sea results in an increased need for understanding their influence on the local atmosphere, as well as the interactions between them. Wind farm operation and power production are affected by wakes produced both within and upstream of the wind farms. Accurately estimating these impacts requires robust mesoscale atmospheric modeling capable of capturing extended wind speed deficits and their dependence on atmospheric stability. This study presents a 3-year-long mesoscale analysis using the Weather Research and Forecasting (WRF) model at a horizontal resolution of 1 km, a comparatively long and high-resolution configuration within the context of offshore wake research. The simulations are evaluated against four lidars located in the Southern Bight of the North Sea in the vicinity of the 3.7 GW
Single- and two-point turbulence spectra derived from wind velocity measurements at a near-coastal site in northern Germany are analysed across a wide range of atmospheric-stability conditions. Spectral estimates are obtained from sonic and cup anemometer data, as well as from velocity time series reconstructed using a system of three synchronized short-range scanning lidars. A high level of agreement is observed at low and intermediate frequencies, with all measurement systems capturing key spectral features, including a plateau under convective conditions and a spectral gap in stable stratification. At higher frequencies, discrepancies arise due to spatial and temporal averaging effects inherent in the lidar and cup anemometer measurements. Spatial coherence estimates are comparatively less affected by these limitations and show high agreement, with exceptions. The synchronized lidar system is found to be highly suitable for coherence analysis, offering flexibility in terms of separation direction, distance, and height. Empirical models are fitted to the auto-spectra and coherence estimates to derive the model parameters as functions of atmospheric stability.