Search Results (35)

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

As the offshore wind industry scales toward 15 MW capacity, the reliability of Direct-Drive Permanent Magnet Synchronous Generators (DD-PMSGs) becomes critical. However, real-world run-to-failure data for these massive, multi-pole machines is virtually non-existent, creating a barrier for developing effective data-driven diagnostic systems. This study proposes a high-fidelity framework for detecting permanent magnet faults in the International Energy Agency (IEA) 15 MW Reference Wind Turbine. Using Finite Element Analysis (FEA), a dataset (magnetic flux and back electromotive-force (EMF)) capturing the electromagnetic signatures of healthy and faulty states of a PMSG under varying severities is generated. To improve the power of computer vision, 1D time-series signals were transformed into 2D images. Specifically, Gramian Angular Fields (GAFs) and Recurrence Plots (RPs) were applied to magnetic flux density signals, while Markov Transition Fields (MTFs) were applied to back-EMF signals. These representations were then fused into multi-channel Red-Green-Blue (RGB) images and processed via a ResNet-18 Deep Transfer Learning model using a strictly non-overlapping, leakage-free dataset partitioning strategy. The proposed framework achieved a classification accuracy of 99.45% on noise-free data. Furthermore, robustness testing under varying levels of Additive White Gaussian Noise (AWGN) (30 dB, 40 dB, and 50 dB Signal-to-Noise Ratio (SNR)) demonstrated sustained high performance, maintaining over 90% accuracy even under severe 30 dB noise conditions. Comparative analysis proved that this multi-channel fusion significantly outperforms single-channel encoding methods, which collapse under heavy noise, validating the scalability of the framework and applicability for next-generation condition monitoring in harsh offshore environments. Full article

Dynamic cables, serving as the critical link between floating wind turbines and submarine cables, are subjected to significant tension fluctuations and bending deformations under environmental loading. While deep-water systems have been widely studied, investigations of large-capacity wind turbines in shallow water environments remain limited. This study establishes a coupled numerical model of an IEA 15 MW floating wind turbine and its dynamic cable system at a water depth of 50 m. The platform’s six-degree-of-freedom motions were calculated under 0°, 90°, and 180° loading directions, followed by a systematic analysis of lazy-wave dynamic cable response characteristics. Results indicate that platform motions and dynamic cable responses are strongly direction-dependent in shallow water, with the 0° loading direction identified as the governing design case due to peak curvature and tension levels. Analysis reveals that the touchdown point location is the primary driver of tension response, while cable length increments predominantly influence bending. Utilizing these insights, a multi-objective fitness function was integrated with a Particle Swarm Optimization (PSO) algorithm. The optimized configuration significantly reduced peak curvature and total cable length, providing a theoretical framework and engineering guidance for the design of high-capacity floating wind systems in shallow-water regions. Full article

To ensure the safety and structural integrity of composite flexible blades under strong winds, this study investigates the extreme aeroelastic responses of the IEA 15 MW wind turbine blade during an emergency shutdown with pitch system faults. Existing studies often rely on simplified models or one-way coupling; we adopt a bidirectional computational fluid dynamics–finite element method (CFD–FEM) fluid–structure interaction (FSI) framework to examine how wind speed and pitch system faults affect aerodynamic loads, displacement responses, and structural stresses when the blade is shut down in a parked-upwind condition. The results reveal that, under the no-pitch condition, the blade experiences extreme loading, with thrust being approximately 15 times higher and the peak stress being 8.6 times that of the pitch condition. Furthermore, a high frequency of 1.969 Hz emerges, significantly increasing the risk of aeroelastic instability as the wind speed increases or under the no-pitch condition. A stress analysis identified that high stress is mainly located in the main spar region, with the peak stress location shifting closer to the blade root under the no-pitch condition. This study highlights the potential risks of composite flexible blades during shutdowns and provides a reference for structural safety design and targeted monitoring. Full article

Offshore wind energy offers substantial potential. However, its inherent intermittency leads to the frequent occurrence of offshore wind energy droughts, which pose challenges to electricity system stability. Mitigation measures aim to reduce the number, duration, or impacts of such droughts. Among the different mitigation approaches, supply-side strategies act directly on wind power generation at the wind farm level. Nevertheless, the effectiveness of supply-side mitigation strategies remains poorly understood. This study addresses these gaps by systematically quantifying the potential of three supply-side mitigation strategies: (i) spatial diversification of wind farm locations, (ii) advances in wind turbine technology, and (iii) reductions in downtime and wake losses, to minimize the number and duration of wind energy droughts across 40 key exclusive economic zones (EEZ) worldwide. Hourly, daily, and monthly drought characteristics for both moderate and extreme offshore wind energy droughts are analyzed using wind data from the ERA5 reanalysis for the period 1993–2022. The results show that spatial diversification across multiple sub-regions is the most effective strategy for mitigating offshore wind energy droughts at the EEZ scale. In addition, the effectiveness of all mitigation strategies exhibits pronounced scale-dependent limitations, which are most evident at the monthly time scale. Overall, this study provides a robust basis for energy-policy decisions and highlights the importance of supply-side mitigation for enhancing the reliability of future electricity systems. 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

Wind turbines are subjected to complex stochastic loadings generated by various environmental sources, including wind, waves, and earthquakes. Efficient mitigation of the resulting vibrations in the structural components, such as the tower and monopile, leads to more cost-effective designs and longer operational life by reducing fatigue accumulation. Conventional vibration control systems have primarily relied on tuned mass dampers. However, alternative and non-conflicting strategies that modify the connection between the tower and the foundation at the transition piece level have recently gained attention. This study investigates the hourglass transition piece (HGTP), a novel concept that utilises the Reduced Column Section approach. The hourglass geometry enables fine-tuning of the wind turbine’s fundamental period and introduces controlled rotational motion, both contributing to a reduction in structural stresses and improved dynamic performance. To assess the efficacy of the HGTP as a vibration control system, an analytical model of a simplified wind turbine is developed. The formulation employs frequency-dependent solutions of prismatic and tapered beam elements, assembled to capture the dynamic behaviour of the turbine equipped with the HGTP. Exact dynamic stiffness matrices are derived and assembled into a stochastic framework suitable for uniformly modulated non-stationary random processes. Modal and dynamic responses are evaluated for different reductions of the hourglass central section. A case study based on the IEA 15 MW Reference Wind Turbine demonstrates that the HGTP can mitigate stochastic mean peak bending moments induced by wind and earthquake excitations by up to 50%, confirming its potential as an effective vibration control solution. Full article

Floating offshore wind turbines (FOWTs) are essential for meeting global renewable energy goals, yet their viability depends strongly on platform motion in harsh marine environments and the resulting influence on structural loading and the levelized cost of energy. This study examines the dynamic response of a 15 MW semi-submersible FOWT based on the IEA-15-240-RWT developed by NREL. The baseline UMaine VolturnUS-S platform is evaluated alongside two newly proposed variants, KSNU-1 15 MW and KSNU-2 15 MW, each equipped with distinct heave-plate configurations designed to enhance hydrodynamic damping while maintaining equal surface area for fair comparison. Hydrodynamic coefficients are obtained through potential-flow analysis using Ansys Aqwa, and fully coupled aero-hydro-servo-elastic simulations are conducted with OpenFAST. The performance of all platforms is assessed under two design load cases (DLCs): the fatigue limit state (FLS) and the ultimate limit state (ULS). The results show that both KSNU platforms achieve slight reductions in surge, sway, and heave motions, with KSNU-2 providing the most consistent improvement in vertical and horizontal stability. Rotational responses increase modestly but remain within acceptable limits. Overall, the KSNU-2 design demonstrates improved motion control without compromising energy output, offering a promising configuration for large-scale floating wind applications. Full article

With the trend towards offshore and larger-scale wind turbines, the increase in blade size makes the trade-off between structural optimization and economic feasibility more critical. To address this issue, this study focuses on the IEA 15 MW offshore wind turbine and investigates the influence of stiffness distribution on its dynamic response, based on the frameworks of multi-body dynamics, the co-rotational beam method, and the free vortex wake method. Results show that blade mid-span stiffness has the most significant influence on system performance. Reducing flapwise bending stiffness increases mean flapwise displacement by 53.8%. This greatly raises the risk of structural damage. Power output is most sensitive to torsional stiffness. Lowering torsional stiffness reduces mean power by 6.9%. This significantly impacts the economic benefits of wind farms. This study contributes to optimizing the structure of large wind turbine blades, enhancing their reliability, and improving cost-effectiveness. Full article

Offshore wind turbines are rapidly scaling in size, which amplifies the need for credible integrated load analyses that consistently resolve the coupled dynamics among rotor–nacelle–tower systems and their support substructures. This study presents a comprehensive ultimate limit state (ULS) load assessment for a fixed jack-up-type substructure (hereafter referred to as K-wind) coupled with the IEA 15 MW reference wind turbine. Unlike conventional monopile or jacket configurations, the K-wind concept adopts a self-installable triangular jack-up foundation with spudcan anchorage, enabling efficient transport, rapid deployment, and structural reusability. Yet such a configuration has never been systematically analyzed through full aero-hydro-servo-elastic coupling before. Hence, this work represents the first integrated load analysis ever reported for a jack-up-type offshore wind substructure, addressing both its unique load-transfer behavior and its viability for multi-MW-class turbines. To ensure numerical robustness and cross-code reproducibility, steady-state verifications were performed under constant-wind benchmarks, followed by time-domain simulations of standard prescribed Design Load Case (DLC), encompassing power-producing extreme turbulence, coherent gusts with directional change, and parked/idling directional sweeps. The analyses were independently executed using two industry-validated solvers (Deeplines Wind v5.8.5 and OrcaFlex v11.5e), allowing direct solver-to-solver comparison and establishing confidence in the obtained dynamic responses. Loads were extracted at the transition-piece reference point in a global coordinate frame, and six key components (Fx, Fy, Fz, Mx, My, and Mz) were processed into seed-averaged signed envelopes for systematic ULS evaluation. Beyond its methodological completeness, the present study introduces a validated framework for analyzing next-generation jack-up-type foundations for offshore wind turbines, establishing a new reference point for integrated load assessments that can accelerate the industrial adoption of modular and re-deployable support structures such as K-wind. Full article

With the growing demand for wind turbines in deep offshore regions, frequent typhoon disasters at sea have impeded the continued development of the wind power industry. To address the problem of typhoons destroying offshore wind power facilities, this paper investigates the aeroelastic characteristics of long flexible blades on ultra-large offshore wind turbines under typhoon loads. The WRF numerical model is employed for high-precision simulations of Typhoon Mangkhut (No. 1822). By optimizing parameterization schemes and incorporating 3DVAR data assimilation techniques, typhoon wind speed profiles in the target sea area are obtained. Based on IEA 15 MW offshore wind turbine data, 3D unsteady CFD models and full-scale finite element models of the blades are established to acquire the aerodynamic loads and structural responses of the blades in typhoon environments. The results indicate that, under extreme typhoon loads and considering wind shear and tower shadow effects, the forces near the blade root are greater; the maximum out-of-plane aerodynamic force occurs at the 14% span position of the blade at 90° azimuth, and the maximum torsional aerodynamic moment is experienced at the 26.5% span position of the blade at 270° azimuth. When the blade pitch angle and rotor yaw angle do not reach ideal states, the deflection of ultra-long flexible blades can increase by up to 3.26 times. These findings overcome the limitations of traditional uniform wind field studies and provide a theoretical basis for subsequent coping strategies for offshore blades under typhoon conditions. 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

Downwind wind turbines offer potential for reduced blade loads and lighter designs, yet systematic aeroelastic comparisons against upwind configurations remain limited, especially for multi-megawatt scales. This study conducts comprehensive OpenFAST simulations of the IEA 15 MW reference turbine in both configurations, contextualized against smaller turbines (2.1, 5, and 10 MW). Scaling trends reveal that, with the increase in turbine size, the disadvantage of the downwind turbine (higher flapwise and edgewise fatigue load) is gradually disappearing and even becomes an advantage. However, downwind configurations amplify tower base loads significantly. These results highlight scalable benefits for blade loads but underscore critical trade-offs requiring tower reinforcement. Optimizing rotor-nacelle mass distribution emerges as a key pathway to mitigate tower penalties while leveraging blade-load alleviation for larger downwind turbines. Full article

The structural integrity of next-generation offshore wind turbines is highly sensitive to inflow variability, yet current standards often simplify wind conditions without capturing their combined effects on dynamic loads. To address this, we analyzed the NREL IEA 15 MW offshore wind turbine using 27 simulation cases strategically selected through Latin Hypercube Sampling (LHS) from a design space of over 14 million combinations. Four key environmental variables—Extreme Wind Speed (30–40 m/s), turbulence intensity (12–16%), Shear Exponent (0.1–0.3), and Flow Inclination Angle (−8° to +8°)—were varied to assess their influence on structural response using BLADED simulations. Results showed that the combined structural moment (Mxyz) ranged from 159,502.5 kNm (minimum) to 189,829.2 kNm (maximum), indicating a 19% increase due to inflow conditions. Maximum-moment case exhibited a 2.6× higher drag coefficient, a 13% rise in pitch bearing moment, and dominant frequency content near 0.175 Hz, closely matching the first tower side-side natural mode (0.17593 Hz), confirming potential resonance. These findings highlight the importance of multidimensional inflow modeling for identifying worst-case load scenarios and establishing a foundation for future load prediction models and support structure optimization. Full article

This study investigates the impacts of surging and pitching motions on the power generation performance and wake characteristics of an IEA 15 MW offshore wind turbine under specific inflow wind conditions. The three-dimensional, unsteady continuity equation, momentum equations, and SST k–ω turbulence model are solved numerically using the computational fluid dynamics software STAR-CCM+ (version 2206) to simulate the aerodynamic flow field around the turbine rotor and in its downstream wake region. Under the condition of an inflow wind speed of 9 m/s at hub height and a corresponding rotor rotational speed of 7.457 RPM, the surging and pitching motions of the turbine are prescribed by sinusoidal functions with a period of 45 s and amplitudes of 2.75 m and 5°, respectively. This study analyzes and quantifies the power output and wake characteristics of the turbine over a duration corresponding to 200 rotor revolutions, considering stationary, surging, and pitching conditions. The results indicate that the surging and pitching motions of the turbine cause reductions in the mean power output of 2.18% and 3.54%, respectively, compared to a stationary condition. The surging and pitching motions also lead to significant wake enhancement in the downstream region, and a minimum spacing of downstream wind turbines is suggested. Full article