When wind passes through the rotor of a wind turbine, the velocity is decreased while turbulence is increased. The region of decreased wind speed behind the rotor is known as the wind turbine wake and is bounded by a complex structure of helical vortices. This structure occurs to be more stable in low ambient turbulence and low tip speed ratio conditions, leading to a delayed recovery of the wake. The diminished wind speed in the wake leads to a decline in power output for downstream wind turbines, with this loss scaling proportionally to the cube of the velocity. This study uses field tests and simulations to evaluate enhanced wake recovery with segmented Gurney flaps on a 3.8-MW research wind turbine. Four Gurney flaps were attached at regions near the tip of each blade. This configuration is hypothesized to induce turbulence that destabilizes the vortex system, resulting in faster wake recovery. Field tests using a scanning LiDAR were conducted to quantify the wind turbine wake recovery between the baseline and the retrofitted configuration in various atmospheric conditions. The results show a consistent increase in wake recovery for the Gurney flap configuration, generally at all downstream distances. This was illustrated by a reduction of axial velocity deficits of roughly 10% at hub height, at five diameters downstream distance. The influence of retrofitting on turbine power and loads was limited. Summarizing, a very successful field test campaign was executed, which demonstrated the use of segmented Gurney flaps as a promising add-on to promote enhanced wind turbine wake recovery for improved overall wind farm performance.

Accurate modeling of atmospheric turbulence is critical for the design and operation of next-generation large-scale wind turbines, particularly those exceeding 15 MW rated capacity and spanning well above the atmospheric surface layer (typically 10 − 20% of the atmospheric boundary layer (ABL)). In this study, Large Eddy Simulations (LES) were performed to investigate turbulence characteristics at high altitudes, up to 300 m above ground level — a region increasingly relevant for large turbine rotors. Turbulence coherence was analyzed and compared with field measurements to assess the fidelity of numerical predictions. Coherence estimates from LES were validated against lidar-based measurements obtained under stable, neutral, and unstable atmospheric conditions. Results show good agreement in the coherence decay rates and cross-spectral characteristics, with notable discrepancies only at very low frequencies (on the order of several 10 ⁻⁴ Hz) and large spatial separations (on the order of several 10 ² m). Consequently, a LES-tuned empirical lateral coherence model is proposed, featuring distinct coherence decay rates for each atmospheric stability regime (stable, neutral, and unstable ABL), offering improved representation of turbulence structures across a range of operating conditions. These findings provide a valuable reference for refining turbulence models for improving load estimation methodologies for next-generation wind turbines operating at hub heights above 200 m.

The accuracy of the Beddoes–Leishman and Risø dynamic stall models is evaluated against experiments on thick wind turbine airfoils with a relative thickness of 35% and trailing edge thicknesses of 10% and 2%, both with and without vortex generators. The dynamic lift, drag, and pitching moment coefficients simulation results are compared with the measurements, obtained in the TU Delft LTT wind tunnel at a Reynolds number of Re=1×10⁶ and dynamic reduced frequency of 0.064. The study revealed that while the aforementioned models successfully predicted the direction of the dynamic cycles, they inaccurately captured the dynamic stall behavior of thick flatback and non-flatback airfoils in all configurations, particularly in separated flows. There was no significant difference observed in the performance of the two models. The reasons for modeling failure are thoroughly examined from both fundamental and mathematical perspectives, and suggestions for improvements are provided. The findings raise concerns regarding the accuracy and reliability of the dynamic load assessment and aeroelasticity analysis for modern large wind turbines, using current dynamic stall models and underscore the necessity for enhancing the existing models.

Engineering wake models are essential tools in wind farm design and operation. Their computational efficiency enables rapid layout optimization, energy calculation, and turbine control setpoint design. As wind farms grow in scale and density, wake interactions between turbines limit overall energy capture and increase structural loading. Wind Farm Control strategies have become critical for mitigating these effects. While wake steering, the intentional yaw misalignment of upstream turbines, has consistently demonstrated power gains, new dynamic control strategies are emerging. Among these, the Helix approach has shown particular promise in accelerating wake recovery and improving downstream power production. While engineering models for wake steering are well established, dedicated models for the Helix approach remain unavailable. This study presents a novel steady-state engineering model for predicting the velocity deficit and added turbulence of wind turbines operating under Helix actuation. The proposed model extends double-Gaussian velocity deficit and bell-curve– shaped turbulence intensity formulations to account for Helix-specific effects of actuation amplitude and ambient turbulence. Calibration and validation against high-fidelity large-eddy simulations demonstrate strong agreement across a wide range of operating conditions. The model accurately reproduces wake recovery trends, variations in the velocity-deficit profile, turbulence distributions, and the resulting downstream power availability. Finally, a case study on a large offshore wind farm illustrates that, under typical offshore atmospheric conditions, Helix control and wake steering yield individual power gains of up to 2.5% and 6.1%, respectively, while their combined application achieves total power gains of up to 7.1%.

During wind turbine installation or idling, the blades often operate at large angles of attack, where vortex-induced vibration (VIV) can occur. This study experimentally investigates the aerodynamic characteristics of a plunging NACA0021 airfoil at a fixed angle of attack of 90∘ and amplitude of one chord length, focusing on vortex dynamics, lock-in effect, and unsteady force generation. Phase-locked particle image velocimetry (PIV) was conducted at two reduced frequencies of 0.19 and 0.38. At the lower reduced frequency, asymmetric vortex shedding prevents synchronization between shedding and plunge motion frequencies, whereas at the higher reduced frequency, lock-in occurs with periodic shedding of separated leading- and trailing-edge vortices. Compared with previously studied surging motion under identical conditions, plunging requires a higher frequency to achieve lock-in and produces weaker wakes that break down more quickly downstream. Additionally, the aerodynamic load is extracted from the PIV flow field. For the plunging motion, the aerodynamic loads are dominated by pressure forces, with a maximum streamwise coefficient of approximately four times the static value at 90∘ angle of attack. This contrasts with the surging motion, where higher force variations are observed, and both pressure and mean momentum convection play comparable roles in the overall force. These results indicate that lock-in behavior depends strongly on both motion frequency and kinematics, where the effective angle of attack variation and the resulting vortex dynamics also determine whether synchronization can occur.

This study experimentally investigates the performance of vortex generators (VGs) designed for steady stall control in preventing unsteady trailing-edge flow separation and dynamic stall during pitch oscillations occurring on inboard and midboard wind turbine blade sections. Surface pressure measurements are conducted in the TU Delft low-speed wind tunnel on a DU-97-W-300 airfoil undergoing pitch oscillations while equipped with VGs of various vane sizes and shapes. In steady conditions, vanes with heights smaller than the local boundary layer thickness optimally balance delaying stall following trailing-edge separation with achieving maximum lift-to-drag ratio among the tested triangular vane VGs. However, these same VGs with vane heights smaller than or equal to the steady local boundary layer thickness are insufficient to suppress the onset and upstream progression of a trailing-edge separation front in all pitching cycles. VGs whose vane height exceeds the local boundary layer thickness for a larger part of the pitch cycle prevent the onset and upstream progression of the trailing-edge separation front for a larger percentage of cycles. Contrary to past literature, rectangular vanes yield a higher steady aerodynamic efficiency than triangular vanes. Rectangular vanes also suppress trailing-edge flow separation in all pitching cycles at all tested reduced frequencies, indicating more effective boundary layer energization than triangular vanes, thus proving to be a better VG shape for steady and unsteady stall suppression on thick airfoils.

Yaw engineering models are commonly used as add-ons to the industrial blade element momentum (BEM) framework to improve load and power predictions by accounting for the skewed wake effect. However, existing yaw engineering models show noticeable limitations in accurately predicting the induced velocity distribution across the blade span. In this study, we employ a genetic symbolic regression （SR） approach to develop a new set of yaw engineering models for both the normal and tangential induced velocities of a static yawed wind turbine. The model regression is performed using simulation data from Reynolds-averaged Navier–Stokes (RANS) simulations with an actuator line model (ALM) of the NREL 5-MW wind turbine, covering a range of yaw angles ((Formula presented.)) and thrust coefficients ((Formula presented.)) over which the skewed wake effect is dominant. The regressed models are selected based on an optimal trade-off between accuracy and complexity, with complexity constrained to remain comparable with Branlard's yaw engineering model. The selected models are subsequently verified using three unseen cases that span different operating conditions and wind turbine models. Verification is performed through a series of evaluations, including generalization performance tests, implementation within the BEM framework to assess their aerodynamic performances, and quantitative errors and loading analyses. The results demonstrate that the proposed models improve both the amplitude accuracy and azimuthal phase of induced velocities compared with the existing models of Coleman and Branlard, enabling it to accurately capture the phase of the peak aerodynamic forces across each annulus and to predict the nonrestoring yaw moment occurring in the inboard region of the turbine, which other models fail to reproduce.

The aerodynamics of the multi-rotor system with lifting-devices (MRSL), an innovative concept of wind energy harvesting machine, is preliminary investigated using Large Eddy Simulation (LES) with actuator techniques. In the current setup, turbulent inflow conditions are considered, but inflow wind shear is excluded. Consistent with previous studies, the results demonstrate faster wake recovery of the MRSL compared to its conventional counterpart, namely the wind turbine system without the lifting-devices. Additionally, a set of high-fidelity simulations further reveals that the enhanced wake recovery is robust under both laminar and turbulent inflow conditions, remaining largely unaffected by variations in the ambient turbulence level. The present work provides proof-of-concept evidence that the effectiveness of MRSLs is not significantly hindered by ambient turbulence, motivating future research to evaluate their performance within a realistic atmospheric boundary layer.

Inspired by Vortex Generators' success in delaying airfoil stall, this study explores the potential of using Vortex Generators to mitigate stall-induced instability in floating offshore wind turbines at parked and skewed inflow conditions for the first time. Significant improvements are achieved by strategically installing Vortex Generators in the outboard sections of turbine blades and optimizing their parameters (normalized height, length, inflow angle, and chordwise positions) using the particle swarm optimization algorithm and fast optimization method. Numerical results, including both linear and nonlinear stall instability analyses, consistently demonstrate that Vortex Generator arrays effectively mitigate stall-induced instability in the edgewise motion of wind turbines. The yaw misalignment angle range corresponding to the occurrence of edgewise instability is reduced by 29.69% (for NREL 5 MW wind turbine) and 22.95% (for IEA 15 MW wind turbine) while also decreasing limit cycle oscillation amplitudes. Additionally, azimuth angle does not influence optimization results, and implementing Vortex Generators can increase the onset wind speed of stall-induced instability without negatively affecting operating conditions.

With the increasing size of floating offshore wind turbines (FOWTs), stall-induced aeroelastic instability has become a critical issue. This study numerically investigates this instability for FOWTs at stand-still conditions using time and frequency domain approaches. A nonlinear aeroelastic model based on quasi-steady theory and a linearized version are used for time and frequency domain simulations, respectively. Hydrodynamic damping considers both radiation and viscous drag effects. The aeroelastic instability of a stand-still NREL OC3-Hywind 5MW FOWT is analyzed for various inflow yaw misalignment angles. Frequency domain simulation shows rotor edgewise and tower side-side modes exhibit stall-induced instability due to aerodynamic negative damping at specific yaw misalignment and azimuth angles. The platform's yaw mode also shows small negative damping, despite large hydrodynamic damping, while other platform modes remain dynamically stable. Safety margins of FOWTs are analyzed for multi-mode stability, and an active control strategy is proposed to prevent stall-induced instability in all unstable modes. Limit cycle oscillations in the rotor's in-out plane are observed from time domain simulation. Instability regions predicted by both analyses highly overlap, but frequency domain results are more conservative. Blade instability may cause high-frequency vibrations in platform movements with limited amplitudes and severe oscillations in tower structures.

This paper studies the dynamic stall characteristics of thick flatback and nonflatback wind turbine airfoils. Two airfoils with a maximum thickness of (Formula presented.) were studied, with trailing edge thicknesses of (Formula presented.) and (Formula presented.), respectively. The static and dynamic experimental measurements were performed in the wind tunnel using surface pressure measurements for clean and tripped airfoils at the Reynolds number of (Formula presented.) and dynamic reduced frequency ranging from (Formula presented.) to (Formula presented.). The effects of the trailing edge gap, roughness, mean angle of attack, and reduced frequency on the dynamic stall characteristics of the airfoils were investigated. The results show that increasing the trailing edge gap delays the onset of dynamic stall. However, the lift loss after the onset of dynamic stall is for the flatback airfoil higher than the sharp trailing edge airfoil. Moreover, the flatback airfoil show higher lift overshoot compared to the sharp trailing edge airfoil in the dynamic stall condition. Increasing the reduced frequency affects the dynamic behavior both airfoils differently.

This study examined the effect of vortex generators on the dynamic stall characteristics of thick wind turbine airfoils with a relative thickness of 35% and trailing edge thickness of 10% and 2%. The experiments were conducted in the TU Delft LTT wind tunnel at a Reynolds number of Re=1×10⁶ and dynamic reduced frequency ranging from 0.032 to 0.096. The study investigated the impact of various factors on the dynamic stall characteristics of the airfoils, including the vortex generator's chord position, trailing edge gap, roughness, mean angle of attack, and reduced frequency. The study found that vortex generators delay dynamic stall for thick airfoils by stabilizing the flow during the upstroke phase. However, this can increase the maximum lift overshoot, particularly with flatback airfoils, resulting in a higher drop in lift during dynamic stall. This can potentially increase the dynamic loads on a wind turbine blade due to stall-induced vibrations. The study noted a significant difference in dynamic stall behavior between flatback and non-flatback airfoils. Overall, this research provides valuable insights into the dynamic stall and flow physics characteristics of thick wind turbine airfoils using vortex generators, aiding in more accurate rotor blade design.

This study presents the experimental validation of regenerative wind farms (RGWFs), a novel wind farm concept designed to enhance overall wind farm performance. RGWFs employ multi-rotor systems with lifting devices (MRSLs), an innovative wind energy harvester engineered to stimulate strong vertical energy entrainment, thereby accelerating wake recovery. In the experiments, MRSLs are scaled for wind tunnel testing, with their rotors modeled using porous disks and their lifting devices represented by wings. The tested RGWFs comprise up to 3 × 3 MRSLs. Flow quantities within RGWFs and aerodynamic loads on MRSLs are measured using volumetric particle tracking velocimetry and strain gauges. Compared to conventional wind farms, flow analysis indicates that vertical energy entrainment is significantly enhanced in RGWFs, as evidenced by a more than 200 % increase in thrust on the second-row MRSLs and so on. These experimental results, which are in line with the previous numerical predictions, highlight the promising potential of RGWFs.

Denser turbine spacing in wind farms leads to increased wake interactions, causing power losses when each turbine operates under its own greedy control scheme. To mitigate these effects, research is exploring strategies that consider the entire wind farm rather than singular turbines. The so-called helix approach has recently gotten significant attention from the research community. It aims to reduce wake losses through periodic individual pitch control. Wake steering on the other hand uses yaw actuation to laterally deflect the wake away from downstream turbines. In this paper, we adapt and validate a steady-state surrogate model to compute the time-averaged velocity field behind a wind turbine operating with the helix approach. The model is tuned using data from Large Eddy Simulations. We compare the helix model to wake steering and baseline operation in a wind farm case study, demonstrating that the helix approach offers promising benefits under specific wind conditions.

Large wind turbines face more intricate atmospheric conditions with turbulent coherent structures sized similarly to the rotor diameter, posing loading challenges. The present study assesses twelve distinct wind fields using the Large Eddy Simulations (LES) and International Electrotechnical Commission (IEC) Kaimal model scaled to their LES counterpart. The hub height wind speed in the different cases was set to 8.5 m/s (below-rated), 11.5 m/s (at-rated), and 14.5 m/s (above-rated). In a previous study, it was found that the unscaled IEC model-based wind field is conservative and scaled IEC model-based wind fields were found to yield different loads than upon use of LES-based wind fields in different atmospheric stability conditions. The present study aims to understand these differences. Utilizing Spectral Proper Orthogonal Decomposition (SPOD), the original wind fields were decomposed and reconstructed to study the influence of large and small coherent structures represented by their distinct frequencies. SPOD analysis was complemented by wind field spectral analysis considering atmospheric surface layer height, integral length scales, and co-coherence estimates. Integral length scales in the scaled IEC Kaimal model were found to be half of those in unstable atmosphere LES wind fields. The aero-elastic impact on the IEA 22 MW reference wind turbine with a 280 m rotor diameter was evaluated. The analysis reveals that large coherent structures, particularly low-frequency (≤0.06 Hz) ones, significantly impact wind turbine loads, contingent upon atmospheric stratification. Compared to the scaled IEC Kaimal model wind field, the maximum tower fore–aft bending moment and the maximum blade root flap-wise bending moment were found to be higher, for example, by 10% and 5% respectively in an unstable atmosphere during below-rated wind turbine operation. In the same scenario, standard deviation of the tower fore–aft bending moment was found to be higher by up to 50% while standard deviation of the blade root flap-wise bending moment was found to be lower by up to 25%. These findings underscore the critical importance of accurately modeling atmospheric turbulence and its coherent structures for more reliable design and operation of large wind turbines.