Search Results (92)

This paper investigates the impact of rotor–nacelle assembly (RNA) structural models on the dynamic response of a 15 MW monopile-supported offshore wind turbine (MOWT). Three RNA models, distributed parameter (DPM), multi-particle (MPM), and concentrated point mass (CPM), were established in ADINA. Model reliability was confirmed through verification against BModes and OpenFAST, covering natural frequencies, mode shapes, and responses under normal environmental loads. The analyses reveal the following: (1) RNA modeling significantly impacts higher-order modal frequencies, with the MPM/CPM exhibiting substantial errors (up to −20.3% and 9.5% for second-order tower mode) and failing to capture blade deformation modes; (2) under low-frequency dominated wave loads, the MPM/CPM predict peak responses within ±10% tolerance; (3) for seismic loads, the discrepancy in three models is governed by input motion spectral characteristics, showing smaller errors under far-field motions (fundamental mode dominated) but significant errors under near-field motions (higher-mode excited). These findings collectively provide theoretical guidance for RNA model selection in MOWTs. Full article

As offshore wind energy advances into deeper waters, the dynamic response and safety assessment of tension leg platform (TLP) wind turbines under complex marine conditions have become focal research points. This study investigates a 15 MW TLP wind turbine, acquiring data on motion responses, mooring tensions, and tower-base loads through time-domain analysis, with extreme value estimation conducted using the mean up-crossing rate method. The results indicate that under normal operating conditions, second-order wave forces significantly influence extreme response estimation. At an exceedance probability of 0.01, the second-order sum-frequency force increases the extreme tower base shear by 4.28% and the bending moment by 10.11% compared to the first-order-only case, while the difference-frequency force has a minor effect. Different wind-wave incidence angles cause distinct variations in turbine motion, with head-on incidence exciting the largest wave-frequency responses and lateral incidence producing relatively weaker excitation effects. Furthermore, the coupling effect between incident direction and second-order wave forces further amplifies extreme response risks. Therefore, it is essential to fully assess the prevailing wind-wave directions in the target sea area and consider the effects of second-order wave forces, especially the sum-frequency component, to ensure the long-term safe operation of TLP wind turbines under complex sea conditions. 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

With the rapidly growing global demand for clean energy, offshore wind power has become an important renewable energy source. To clarify how the principal dimensions affect the performance of a 15 MW-class floating wind turbine platform in 100 m water depth, this paper proposes a steel-concrete hybrid semi-submersible platform and systematically performs a parametric sensitivity analysis. The platform adopts a three-column configuration with heave tanks. The upper columns and cross braces are made of steel, while the lower hexagonal columns, pontoons, and heave tanks are constructed from concrete, significantly reducing steel consumption while satisfying structural and stability requirements. Focusing on three key design variables—draft, column spacing, and column diameter—this study establishes a unified normalized sensitivity analysis framework. It quantitatively evaluates their influence on platform mass, intact stability, natural periods, and fully coupled dynamic responses (including surge, heave, pitch motions, and mooring line tensions) under both operational and extreme conditions. The results reveal distinct roles of the principal dimensions in governing the platform dynamics: column spacing is the most sensitive parameter for tuning pitch response, restoring stiffness, and stability; increasing draft effectively suppresses heave and pitch responses but has only a limited effect on low-frequency surge motions; and column diameter strongly affects the natural periods of heave and pitch. Notably, dynamic responses exhibit significant nonlinear characteristics with variations in column diameter. When the diameter exceeds 110–120% of the baseline value, the peak pitch response under extreme sea states shows a deteriorating inflection point, accompanied by an accelerated surge in peak mooring loads. This indicates that excessive increases in column diameter may cause wave excitation forces to become dominant, thereby compromising the overall dynamic safety of the system. This paper identifies the governing geometric parameters for different motion modes and their control boundaries, providing a quantifiable and generalizable basis for the multi-objective collaborative design and cost reduction optimization of 15 MW steel-concrete hybrid semi-submersible floating wind turbine platforms. Full article

The upscaling of turbines in the offshore wind industry has been unprecedented, as compared to 5–6 MW rated turbines 10 years ago. A typical 20–26 MW rated turbine in modern commercial applications (MingYang MySE 18.X-20 MW installed in 2025 and 26 MW prototype by Dongfang Electric tested in 2025) has been demonstrated. This scaling has been made possible by increasing rotor diameters (>250 m) and hub heights (>150–180 m) to achieve capacity factors of up to 55–65%, annual energy generation of more than 80 GWh/turbine, and significant decreases in levelised cost of energy (LCOE) to current values of up to 63–65 USD 2023/MWh globally averaged in 2023 (with minor variability in 2024 due to market changes and new regional areas). The paper analyses turbine upscaling over three levels of hierarchy, including turbine scale—rated capacity and physical aspect, project scale—multi-gigawatts of farms, and market scale—the global pipeline > 1500 GW level, and combines techno-economic evaluation, structural evaluation of loads, and infrastructure needs assessment. The upscaling has the advantage of reducing the number of turbines dramatically (e.g., 500 to 67 turbines in a 1 GW farm, as turbine size is increased to 15 MW) and balancing-of-plant (BoP) CAPEX (turbine-to-turbine foundations and cables) by some 20 to 30 percent per unit of capacity, and serial production learning rates of between 15 and 18% per doubling of capacity. But the problems that come with the increase in ultra-large designs are nonlinear increments in mass and load (i.e., blade-root and tower-bending moments), logistical constraints (blades > 120 m, nacelle up to 800–1000 tonnes demanding special vessels and ports), supply-chain issues (rare-earth materials, vessel shortages increase day rates by 30–50%), and technology limitations (aeroelastic compounded by numerical differences between reference 5 MW, 10 MW, and 15 MW models), it becomes evident that there is a significant increase in deflections of the tower and blades and platform surge/pitch responses with continued increases in power levels, but without a correspondingly mature infrastructure. The regional differences (mature ports of Europe vs. U.S. Jones Act restrictions vs. scale-up of vessels/manufacturing in China) lead to the necessity of optimisation depending on the context. The analysis concludes that, to the extent of mature markets with adapted logistics, continuous upscaling is an effective business strategy and can result in 5 to 12 percent further reductions in LCOE, but beyond that point, gains become marginal or even negative, as risks and costs increase. The competitiveness of the future depends on multi-scale/multi-market-based approaches—modular-based families of turbines, programmatic standardisation, vibration control innovations, and industry coordination towards supply-chain alignment and standards. Its major strength is that it transcends mere size–cost relationships and shows how nonlinear structural processes, aero-hydro-servo-elastic interactions, and bottlenecks in logistical systems are becoming more determinant of the efficiency of ultra-large turbines. The study demonstrates that upscaling turbines has LCOE benefits through the support of associated improvements in installation facility, supply-chain preparedness, and structural vibration control potential, based on the comparisons of quantitative loads, techno-economic scaling trends, and regional market differentiation. Full article

Wind power has experienced rapid development due to its renewable advantages. To address the performance degradation of wind turbines caused by icing in alpine regions, this study integrates field testing and numerical simulation to analyze three key aspects for a 1.5 MW turbine: the underlying mechanism of icing impact, the effect of a de-icing coating on performance during ice-free operation, and the coating’s efficacy under active icing conditions. Results show that ice accretion causes a 25% power loss, induces severe flow separation and vortex shedding, and shifts the separation point forward to 15% chord length. Under ice-free conditions at an average wind speed of 8.3 m/s, the de-icing coating introduces a negligible power deviation of only 0.4%. In extreme cold, ice thickness on the coated blade section was measured at just 4.86 cm. The research demonstrates that de-icing the outer 10 m blade tip section substantially improves performance and confirms that the coating has a minimal aerodynamic footprint during normal operation while providing effective ice mitigation. These findings offer a scientific foundation for optimizing de-icing techniques and support the broader application of such coatings for wind turbines in cold climates. 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

Floating offshore wind turbines (FOWTs) exhibit complex motions under marine environmental loads and frequently undergo coupled oscillations across multiple degrees of freedom (DOFs). Accurate short-term motion prediction of these responses is crucial for operational safety and maintenance. To overcome the limitations of traditional “black-box” models under complex aero-hydrodynamic loads, this study proposes STL–TimesNet–NLinear, a novel physics-informed deep learning framework. The framework utilizes STL decomposition to explicitly decouple motion signals: NLinear captures non-stationary low-frequency slow drifts, while TimesNet extracts multi-periodic wave-frequency responses. The model was evaluated across different platform typologies—a 5 MW semi-submersible and a larger-scale 15 MW Spar-type platform—under various typical operational and extreme environmental conditions. Model performance was evaluated using comparative and ablation experiments. At a prediction-ahead time (PAT) of 5 s, the proposed model achieves coefficients of determination (R²) exceeding 0.95. Even at longer PATs, the R² remains above 0.90, consistently outperforming multiple benchmark models. Compared to traditional recurrent neural networks (e.g., LSTM), it decreases the Mean Absolute Error (MAE) for pitch motion under extreme sea states by 54.7% and increases the R² to 0.9573. Furthermore, the inference latency is only 2.4 ms per step. These findings confirm that the proposed STL–TimesNet–NLinear model provides fast and accurate solutions for the short-term motion response prediction of FOWTs, demonstrating valuable potential applications for enhancing the safety planning of offshore wind turbine operation and maintenance. 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

Southern Patagonia in Argentina possesses a world-class wind resource; however, its remote location challenges long-term monitoring. This study presents the first long-term Doppler LiDAR-based wind characterization in the region, analyzing six months of high-resolution data at a 100 m hub height. Power for the LiDAR is provided by a hybrid system combining photovoltaic (PV) and grid sources, with remote monitoring. The results reveal two distinct seasonal regimes identified through a multi-model statistical framework (Weibull, Lognormal, and non-parametric Kernel Density Estimation: a high-energy summer with concentrated westerly flows and pronounced diurnal cycles (Weibull scale parameter A ≈ 11.9 m/s), and a more stable autumn with a broad wind direction spectrum (shape parameter k ≈ 2.86). Energy output, simulated using Windographer v5.3.12 (Academic License) for a Vestas V117-3.3 MW turbine, shows close alignment (~15% difference) with the operational Bicentenario I & II wind farm (Jaramillo, AR), validating the site’s wind energy potential. This study confirms the viability of utility-scale wind power generation in Southern Patagonia and establishes Doppler LiDAR as a reliable tool for high-resolution wind resource assessment in remote, high-wind environments. Full article

Offshore wind energy is a key enabler of the global net-zero transition. As nearshore fixed-bottom projects reach maturity, floating offshore wind turbines (FOWTs) are becoming the next major focus for large scale deployment. To accelerate this development and reduce construction costs, it is essential to optimize mooring systems through a systematic and performance driven framework. This study focuses on the mooring assessment of the Taiwan-developed DeltaFloat semi-submersible platform supporting a 15 MW turbine at a 70 m water depth offshore Hsinchu, Taiwan. A full-chain catenary mooring system was designed based on site specific metocean conditions. The proposed framework integrates ANSYS AQWA (version 2024 R1) and Orcina OrcaFlex (version 11.5) simulations with sensitivity analyses and performance-based fitness metrics including offset, inclination, and line tension to identify key parameters governing mooring behavior. Additionally, an analysis of variance (ANOVA) was conducted to quantitatively evaluate the statistical significance of each design parameter. Results indicate that mooring line length is the most influential factor affecting system performance, followed by line angle and diameter. Optimizing these parameters significantly improves platform stability and reduces tension loads without excessive material use. Building on the optimized symmetric configuration, an asymmetric mooring concept with unequal line lengths is proposed. The asymmetric layout achieves performance comparable to traditional 3 × 1 and 3 × 2 systems under extreme environmental conditions while demonstrating potential reductions in material use and overall cost. Nevertheless, the unbalanced load distribution highlights the need for multi-scenario validation and fatigue assessment to ensure long-term reliability. Overall, the study establishes a comprehensive and sensitivity-based evaluation framework for floating wind mooring systems. The findings provide a balanced and practical reference for the cost-efficient design of floating offshore wind farms in the Taiwan Strait and other shallow-water regions. 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

Predicting structural loads on offshore wind turbine support structures under varying environmental conditions is a complex yet critical task, particularly for large-capacity turbines such as the 15 MW offshore wind turbine. Current prediction methods often struggle with accuracy, especially for torsional moments, due to the non-linear interactions between wind parameters and structural responses. To address this challenge, present study develops a generalized load estimation framework using multivariable polynomial regression, leveraging 10,000 numerical simulations. The framework accounts for four critical variables: Extreme Wind Speed (30 to 40 m/s), Turbulence Intensity (12% to 16%), Flow Inclination Angle (−8° to +8°), and Shear Exponent (0.1 to 0.3). The proposed equations predict six key moment components at the tower base, including the bending moments about the y-axis, torsional moments about the z-axis, bending moments in the x-y, x-z, and y-z planes, and the resultant combined moment. The framework was validated using 2000 testing data points, achieving high accuracy with R² values exceeding 0.92 for all moments. Specifically, the prediction accuracy was highest for the resultant combined moment and y-z bending moment, with average absolute errors of 5.76% and 5.97%, respectively, while x-z bending moment had a slightly higher error of 13.91%, highlighting that torsional moments are inherently more challenging to predict. Heatmap and scatter plot analyses confirmed that the predicted moments align closely with the simulated values, particularly for the torsional moment about the z-axis and y-z bending moment, with standard deviation values as low as 4.85. By optimizing polynomial degrees between 2 and 4, the framework effectively balances prediction accuracy and computational efficiency. This approach provides engineers and scientists with a reliable tool for load estimation, facilitating improved design and analysis of offshore wind turbine support structures. Full article