Search Results (92)

This paper analyzes the fatigue loads of wind turbines in a floating offshore wind farm (FOWF) whose layout can be reconfigured. Such wind farm reconfiguration will be useful for wake effect mitigation in varying wind conditions. As an example FOWF, a farm with three 5 MW floating offshore wind turbine (FOWT) models on semi-submersible platforms, developed by the National Laboratory of the Rockies (NLR) (formerly the National Renewable Energy Laboratory (NREL)), is considered. Simulations for the example FOWF are conducted with various realistic turbulent wind and irregular wave conditions in the medium-fidelity wind farm simulator FAST.Farm. Using the simulation data, fatigue analysis is conducted by calculating the damage equivalent loads (DELs) using the computational tool MLife at critical components of the three FOWTs. The analysis results demonstrate the potential of reconfigurable FOWFs in not only increasing power outputs but also reducing fatigue loads for many critical components of turbines. Full article

Accurate performance prediction for large offshore wind turbines requires a principled treatment of uncertainty in both the wind resource and the rotor design parameters. In the present work, we develop a surrogate-based, multi-level uncertainty quantification (UQ) framework coupling a physics-based Blade Element Momentum (BEM) solver with a spectral Polynomial Chaos Expansion (PCE) surrogate that replaces the expensive Monte Carlo loop and apply it to the IEA 15 MW offshore reference wind turbine. The framework is completed by Sobol variance-based global sensitivity analysis. The contribution is methodological rather than algorithmic: although each individual ingredient (PCE, Sobol, BEM, and Jensen) is well established, their joint deployment in a single, internally consistent, end-to-end probabilistic workflow that simultaneously delivers (i) aerodynamic–structural UQ with analytical Sobol ranking, (ii) a like-for-like cross-comparison of three reference turbines, (iii) a quantitative leading-edge icing degradation study, and (iv) a farm-level wake-steering optimization on the same IEA 15 MW reference rotor yields a unified probabilistic envelope from which manufacturing tolerances, cold-climate investment thresholds, and farm-layout/control trade-offs can be read off consistently. Five input parameters are treated as random variables: hub-height wind speed (Weibull, k = 2.2, c = 9.8 m/s), air density, blade chord length, twist angle, and rotor speed. A degree-4 sparse PCE is built by non-intrusive spectral projection using N = 5000 Sobol quasi-random realizations, which allows the Sobol indices to be recovered analytically from the expansion coefficients at essentially no extra cost. Three parallel engineering studies complement the core UQ analysis: (A) a head-to-head comparison of the NREL 5 MW, DTU 10 MW, and IEA 15 MW reference turbines; (B) a quantitative assessment of leading-edge ice accretion at four severity levels; and (C) a Jensen-based wake optimization for a 25-turbine offshore array with static wake steering. The main results are as follows: the turbine reaches C_p,max = 0.480 at λ_opt = 8.51, and an annual energy production (AEP) of 71,261 MWh/year (PCE: 70,840 ± 2,140 MWh/year, 95% CI). Wind speed emerges as the dominant driver of C_p variance (S₁ = 0.412), followed by blade twist (0.198) and chord (0.143). Severe icing (30 kg/m) reduces C_p by 18.2% and increases the blade-root Damage Equivalent Load (DEL) by 18.5%. For the array, the optimal spacing (s_x = 8D, s_y = 6D) gives a farm efficiency of 89.6% and 1296 GWh/year, and a 15° wake-steering offset adds a further +3.2% to farm AEP. Compared with plain Monte Carlo, the sparse PCE delivers the same statistics with about 36% fewer model evaluations and a relative error below 0.8%. Full article

Wind energy is one of the clean and sustainable energy sources that can be used to meet global energy demand. However, although wind turbines are used to harness energy in coastal and offshore areas, the extreme environmental conditions make it difficult to utilize these structures optimally and also negatively impact their safety. Therefore, in this study, the yaw angles of the National Renewable Energy Laboratory (NREL) 5 MW wind turbine mounted on a monopile platform were controlled using a Long Short-Term Memory (LSTM) artificial intelligence (AI) architecture to optimize power output and ensure structural stability against dynamic responses under irregular wave and Izmir–Samos tsunami conditions. First, the İzmir–Samos tsunami, the NREL 5 MW wind turbine mounted on a monopile platform, the analytical methods employed, the LSTM architecture, and the parameters used in the study were described. The results of the wind direction time series prediction and the aerodynamic, hydrodynamic, and structural responses of the LSTM-based yaw angle control strategy on the wind turbines were investigated and discussed. According to the results, the increase in aerodynamic power achieved using the LSTM-based strategy was approximately $5.18\%$ under a scenario with constant wind speed and variable wind direction in two different sea conditions and $5.29\%$ under conditions of irregular waves with fully variable wind speed and direction. In addition, more stable responses were observed for most of the parameters examined. The primary goal of this study is to serve as a reference for researchers working on AI-optimized power output and response analysis resulting from varying the yaw angles of wind turbines. Full article

This paper presents AeroelasticQ, a modular, high-performance aeroelastic simulation code for wind turbines, with particular emphasis on future applicability to multi-rotor configurations. The framework is organized into three core components: a flexible-blade structural solver, an airfoil-based aerodynamic solver, and a two-mesh aero-structural mapping module for transferring loads and kinematics between the aerodynamic and structural discretization. The implementation is written in C++17 using the Eigen linear algebra library (v5.0.0), and OpenMP (v5.1) is employed to enable rotor-level parallel execution for multi-rotor applications. The structural dynamics are formulated using Kane’s dynamic method combined with modal superposition, while the aerodynamic loads are computed using three-dimensional blade element momentum theory. The coupled and uncoupled modules are validated in the time domain against OpenFAST (v4.1.2) AeroDyn, ElastoDyn, and the coupled AeroDyn–ElastoDyn configuration using the NREL 5 MW reference wind turbine. The rotor-level aerodynamic validation gives mean absolute errors of 8.94 × 10⁻⁴, 2.82 × 10⁻⁴, and 2.71 × 10⁻⁵ for C_t, C_p, and C_q, respectively, while the coupled aeroelastic cases show close agreement in blade tip deflections, blade root loads, and aerodynamic power. A rigid three-rotor verification confirms the multi-rotor load-aggregation framework, with tower base thrust and overturning moment errors below 1.5% and 2% NRMSE, respectively, in both all rotors operating and one operating/two-parked configurations. In single-thread benchmarks, AeroelasticQ achieves speedups of 5.23×, 19.69×, and 3.65× in the aerodynamic-only, structural-only, and fully coupled modes, respectively. In the multi-rotor benchmark, the five-rotor case achieves a parallel speedup of 2.55× with a parallel efficiency of 51%. Full article

Spar-type floating offshore wind turbines (FOWTs) operating in deep-sea environments are subjected to coupled wind and wave excitations spanning a wide frequency range, rendering single-frequency passive damping solutions inadequate. A folded-beam nonlinear energy sink (FB-NES) is proposed for broadband vibration suppression of spar-type FOWTs. The device employs pre-buckled elastic beam arms integrated with constrained layer damping patches, and a closed-form analytical relationship between the beam geometric parameters and the nonlinear stiffness coefficients is derived, enabling direct parameter design without iterative calibration. The pre-buckled geometry introduces a negative-stiffness mechanism that substantially lowers the targeted energy transfer (TET) threshold, ensuring device engagement under all normal operational sea states. A 14-degree-of-freedom aero-hydro-elastic model of the NREL 5 MW OC3-Hywind FOWT with the FB-NES is established via the Euler–Lagrange formulation and validated against OpenFAST. Based on the numerical results under operational and extreme parked load cases, the FB-NES achieves substantial broadband vibration reductions that grow monotonically with wave severity, consistently and substantially surpassing both the optimally tuned mass damper (TMD) and a conventional cubic nonlinear energy sink of equal mass. Wavelet analysis confirms that targeted energy transfer, rather than direct viscous damping, is the dominant energy dissipation mechanism. The FB-NES also maintains effective control over a wide frequency detuning range, demonstrating superior robustness compared to the TMD. Full article

Stable wind resources in far-reaching sea areas are important direction for the development of renewable energy, making floating offshore wind turbine (FOWT) a focus of current research. However, the working environment of FOWT is severe. Under the condition of changeable wind and waves, the floating platform exhibits various motion responses, which may reduce power generation efficiency and even lead to structural damage with unpredictable consequences. In this paper, the National Renewable Energy Laboratory (NREL) 5 MW OC4-DeepCwind semi-submersible wind turbine is considered, and a multi-degree-of-freedom (M-DOF) tuned mass damper (TMD) system is designed to simultaneously suppress its roll and pitch motion responses. A multi-objective optimization problem is formulated to unify the frequency tuning accuracy, damping ratio constraints, and mass ratio limits through penalty functions. Then an improved Particle Swarm Optimization algorithm with time-varying acceleration coefficients (TVAC-PSO) is employed to determine the optimal TMD parameters, which dynamically adjusts exploration and exploitation capabilities to overcome the limitations of standard PSO in handling the strongly coupled parameter space. A high-fidelity aero-hydro-servo-elastic simulation model is established using OpenFAST to verify the vibration suppression performance under various sea state conditions. Simulation results demonstrate that the proposed M-DOF TMD system can effectively reduce the roll and pitch motion responses and significantly suppress the resonant peak energy, substantially improving the dynamic performance of FOWT. Full article

This study presents a numerical investigation of the effects of atmospheric icing on the aerodynamic performance and power output of the NREL 5 MW reference wind turbine. In cold climate regions, ice accretion on wind turbine blades significantly alters the airfoil geometry, leading to aerodynamic degradation characterized by increased drag, reduced lift, and substantial power losses. Understanding these effects is therefore essential for reliable performance prediction and efficient turbine operation under icing conditions. To address this problem, numerical simulations were conducted on six representative blade sections using the FENSAP-ICE framework, which integrates flow field calculations, droplet transport, and ice accretion modeling within a unified computational environment. The analyses were performed under different atmospheric icing conditions, considering liquid water content values of 0.22 g/m³ and 0.50 g/m³ and ambient temperatures of −2.5 °C and −10 °C. The median volumetric diameter was fixed at 20 µm, and the icing duration was set to one hour for all cases, allowing for both glaze and rime ice formations to be systematically examined. The results reveal that ice accretion becomes increasingly pronounced toward the blade tip, mainly due to higher relative velocities and increased collection efficiency in the outer sections. Glaze icing conditions produce irregular horn-shaped ice formations and lead to severe aerodynamic degradation, whereas rime ice forms more compact structures near the leading edge and results in comparatively lower performance losses. The degraded aerodynamic coefficients obtained from the iced airfoils were subsequently incorporated into BEM-based power calculations, indicating that total power losses can reach up to 40% under severe icing conditions, with the outer blade sections contributing most significantly to this reduction. Furthermore, an economic assessment based on annual energy losses highlights the substantial impact of atmospheric icing on wind turbine performance and operational costs. Full article

Offshore wind energy is an attractive renewable energy source due to its advantages. However, the chaotic marine environment makes the analysis of offshore wind energy extremely difficult. Furthermore, studying the behavior of wind turbines under rare and hazardous natural events such as rogue waves is crucial for the safety and operation of wind turbines and the platforms mounted on them. Therefore, this study numerically investigates the aerodynamic, hydrodynamic, and structural properties of the National Renewable Energy Laboratory (NREL) 5 MW wind turbines under the effect of the Draupner wave, the first marine rogue wave ever recorded. To this end, the geometric and structural information of the NREL 5 MW wind turbines mounted on monopile and jacket platforms is explained. The characteristics of the Draupner wave and the variations in its wave height time series are investigated. The recorded wave height time series values are imported into the QBlade program, and the dynamics of NREL 5MW monopile and jacket wind turbines are simulated. Based on the simulation data, the aerodynamic, hydrodynamic, and structural properties of these structures are examined and analyzed. The results demonstrate that Draupner waves have a significant effect on the aerodynamic, hydrodynamic, and structural parameters of the wind turbines. These parameters are observed to reach their highest values, particularly between the 250th and 280th seconds, when the Draupner wave height reaches its peak. Our findings indicate that the jacket structure experienced higher total forces due to its larger wetted surface area and geometric complexity, while the monopile foundation showed higher inertial loading in the X-direction because of its larger added mass. Additionally, we observed that total aerodynamic power generation is significantly affected by the passage of the Draupner rogue wave. We discuss our findings and their limitations. This numerical study is intended to be a milestone for researchers working on the structural health of offshore wind turbines and platforms under the effect of rogue waves. Full article

The increasing scale and structural flexibility of modern wind turbine rotors have made real-time monitoring and active control of blade tip deflection a critical requirement for ensuring operational safety, particularly regarding blade-tower clearance. Since direct measurement through physical sensors is often impractical due to high costs, installation difficulties and maintenance challenges, this work proposes a data-based framework for out-of-plane blade tip deflection estimation. The approach introduces a systematic and hierarchical input selection framework that evaluates sensor signal groups, ranging from standard SCADA measurements to configurations including auxiliary nacelle/tower sensors and dedicated blade-root instrumentation. By combining Spearman correlation and spectral coherence, the proposed framework ensures consistent representation of key turbine dynamics across all operating regions. This framework provides a structured trade-off between implementation feasibility and estimation fidelity, enabling tailored solutions for applications such as structural health monitoring and safety-critical active control. Compact Feedforward Neural Network (FNN) and Time-Delay Neural Network (TDNN) architectures, whose hyperparameters are optimized via Bayesian optimization, are employed to achieve high estimation accuracy while preserving computational efficiency. Evaluated through high-fidelity aeroelastic simulations of the NREL 5 MW turbine using the industry-standard FAST (Fatigue, Aerodynamics, Structures, and Turbulence) tool across all operating conditions, the approach achieves $R^2=0.894$ using SCADA-only inputs, $R^2=0.973$ when augmented with nacelle and tower-top sensors and a peak fidelity of $R^2=0.989$ using blade-root bending moment data. These results demonstrate that high-fidelity virtual sensing is attainable without blade instrumentation, providing a viable pathway for real-time tip clearance monitoring and fatigue mitigation. This directly enhances the operational resilience of wind energy systems and their contribution to the stability of renewable-dominated power grids. Full article

In the analysis and design of wind turbines, aeroelastic analysis is required that considers elastic structure and control in addition to aerodynamic characteristics. In recent years, with the increase in size and reduction in the cost of wind turbines, problems have emerged that cannot be addressed with the standard analysis methods. The accuracy of the Blade Element and Momentum (BEM) theory, which is the most common aerodynamic analysis and design theory, is reduced in conditions where three-dimensional effects such as radial flow are not negligible. Furthermore, full-model Computational Fluid Dynamics (CFD), which is commonly used for complex aerodynamic problems, is not applicable for the design calculation of wind turbines considering itscomputational demands. To address these challenges, the Actuator Line Model (ALM) can be utilized as practical load analysis methods that account for structural elasticity, control, and fluctuating winds—offering a level of fidelity between both approaches. However, the conventional ALM does not account for the stall delay (SD) observed in the inboard section of rotor. In this study, an ALM based on CFD is developed by incorporating Snel’s stall delay model, which was developed for BEM. Additionally, the use of the NREL 5 MW reference wind turbine rotor results in the load distribution of the inboard section of this developed model to be comparable to that of the full-model CFD; however, a similar observation is not made for the conventional BEM. Full article

Floating offshore wind turbines (FOWTs) are subjected to complex oceanic environmental loads, which can result in non-collinear wind and wave directions that may not align with the rotor axis, potentially leading to complex variations in aerodynamic characteristics. In this study, the aerodynamic performance and wake of the NREL 5 MW wind turbine under different inflow angles and platform surge motions in various directions were investigated using the actuator line model (ALM) implemented in OpenFOAM. The results demonstrate that an increase in surge amplitude primarily amplifies the cyclic fluctuations in rotor thrust and torque, while the direction of surge motion has a negligible influence. In contrast, yawed inflow leads to a substantial reduction in both the mean and peak values of thrust and torque. Wake analysis further reveals that the mean wake recovery is predominantly governed by the yaw angle. Under aligned inflow conditions, the wake remains nearly symmetric and shows limited sensitivity to platform surge motion. Conversely, yawed inflow induces significant wake deflection with an asymmetric distribution of turbulent kinetic energy and enhanced mixing in the downstream region. Full article

Leading-edge erosion of wind turbine blades caused by repeated raindrop impingement can significantly reduce power output and increase maintenance costs. This study develops a rain erosion atlas for Japan over 11 years from 2006 to 2016 based on the CRIEPI-RCM-Era2 dataset. The NREL 5 MW, DTU 10 MW, and IEA 15 MW wind turbines were employed to evaluate the incubation time (erosion onset time) of commercial polyurethane-based coating at the blade tip. Erosion progression was simulated using an empirical damage model that relates raindrop impingement and impact velocity to the incubation time. The rain erosion atlas reveals a clear correlation between wind turbine size and erosion risk: the NREL 5MW turbine shows an incubation time of 3–12 years, the DTU 10MW turbine 1–4 years, and the IEA 15MW turbine 0.5–2 years. Shorter incubation times are observed on the Pacific Ocean side, where annual precipitation is higher than on the Sea of Japan side. Additionally, the influence of coating degradation due to ultraviolet radiation was assessed using solar radiation data, revealing a further reduction in incubation time on the Pacific Ocean side. Finally, the potential of erosion-safe mode operation was examined, demonstrating its effectiveness in alleviating erosion progression. Full article

When operating in the marine environment, floating offshore wind turbines (FOWTs) are subjected to various inflow conditions such as wind, waves, and currents. To investigate the effects of complex inflow conditions on offshore wind farms, an integrated fluid-structure interaction computational and coupled dynamic analysis method for FOWTs is employed. An aero-hydro-servo-elastic coupled analysis model of the NREL 5 MW semi-submersible wind turbine array based on the OC4-DeepCwind platform is established. The study examines the variations in power generation, platform motion, structural loads, and flow field distribution of the FOWT array under different wave incident angles and yaw angles of the first column turbines. The results indicate that the changes in power generation, platform motion, and flow field distribution of the wind farm are significantly influenced by the yaw angle. The maximum tower top yaw bearing torque and the tower base Y-direction bending moment of the wind turbines undergo significant changes with the increase in the angle between wind and wave directions. The study reveals the mechanism of power generation and load variation during yaw control of the FOWT array under misaligned wind and wave conditions, providing a theoretical basis for the future development of offshore floating wind farms. Full article

With the increase in size and flexibility of wind turbines, the safety of large wind turbines becomes a major issue. For this reason, a novel 15-degree-of-freedom (DOF) large wind turbine reduced-order model is proposed in this paper based on the Euler–Lagrange equation. Considering rated speed and parking operating conditions, the dynamic response of the large wind turbine under multidimensional seismic excitation is studied. The 5 MW fixed-bottom wind turbine developed by the National Renewable Energy Laboratory (NREL) is used to testify to the effectiveness of the proposed model. The simulation results indicate that the modal frequencies of the new 15-DOF dimensionality reduction model have a relative error of 0.128–7.820% compared with FAST results, the maximum displacement in the flapwise direction of the blade is 64.93% greater than that in the edgewise direction, and the maximum acceleration is 91.47%. Considering the vertical seismic excitation, the maximum displacement of the edgewise direction is increased by 48.45%, the maximum acceleration of the edgewise direction is increased by 161.17%, the maximum vertical displacement at the top of the tower is within 0.07–0.50% of the horizontal displacement, and the maximum vertical acceleration at the top of the tower is within 5.01–14.42% of the horizontal acceleration. The rated speed state is the worst operating condition in the edgewise direction of the blade, and the maximum blade edgewise acceleration is increased by 180.36% compared with the parking state. The parking state is the worst operating condition in the flapwise direction of the blade, and the maximum blade flapwise acceleration is increased by 365.51% compared with the rated speed state. Full article

Fatigue damage of yawed wind turbine components can be caused by repeated long-term unsteady asymmetric inflow loads across the rotor swept area, necessitating fatigue load analysis to ensure the in-operation safety of wind turbines. This study investigates the impact of geometric nonlinearity on the fatigue loads of wind turbine components. The geometrically exact beam theory (GEBT), implemented in BeamDyn of OpenFAST, is employed to model full geometric nonlinearity. For comparison, ElastoDyn in OpenFAST, which uses the generalized Euler–Bernoulli beam theory for straight isotropic beams, is also utilized. Aeroelastic simulations were conducted for the national renewable energy laboratory (NREL 5 MW) and international energy agency (IEA) 15 MW wind turbines. Fatigue loads, quantified by the damage equivalent load (DEL) based on Palmgren–Miner’s rule, were analyzed for critical components, including blade out-of-plane (OOP) moments, low-speed shaft (LSS) torque, LSS bending moment (LSSBM), and tower base bending moment (TBBM). Results indicate that geometric nonlinearity significantly influences fatigue damage in critical turbine components, with significant differences observed between BeamDyn and ElastoDyn simulations. Full article