Wind Turbine Blades Research Articles

A Critical Review on the Structure and Recovery Technologies of End-of-Life Wind Turbine Blades

A Critical Review on the Structure and Recovery Technologies of End-of-Life Wind Turbine Blades

Concepts of Reusing Wind Turbine Blades in Civil Engineering Constructions

Wind turbines have become an important source of renewable energy in recent years, but recycling them is difficult due to their material properties. The paper indicates the possibility of using turbine blades to produce elements that can be filled with concrete and used as members of small geotechnical structures: retaining walls, point and well foundations, foundations for railings, fences, road signs, etc., as well as excavation linings and shoring walls. In these solutions, concrete-filled elements of turbine blades constitute a form (formwork) for concrete, protecting it against environmental influences, and can also cooperate with concrete in transferring loads.

Lightweight algorithm based on you only look once version 5 for multiple class defect detection on wind turbine blade surfaces

A lightweight wind turbine blade surface multiple class defect detection algorithm based on You Only Look Once version 5 (YOLOv5) is proposed to address the issues of low accuracy, poor efficiency, and high power consumption associated with manual and traditional automation algorithms used for detecting surface defects on wind turbine blades. Firstly, by replacing the Concentrated-Comprehensive Convolution Block module in YOLOv5 with the GhostBottleneckv2 module, the overall parameter count of the model is significantly reduced. Additionally, advocating the inclusion of the Convolutional Block Attention Module (CBAM) into the YOLOv5 backbone network to address the issue of small targets and significant scale variations in surface defects found on wind turbine blades. The YOLOv5 feature fusion module replaces the Feature Pyramid Network (FPN) structure with the Bidirectional Feature Pyramid Network (BiFPN) structure to enhance the fusion capability of multi-scale weighted features. Finally, the optimized model files underwent structured pruning through the application of pruning strategies, retraining fine-tuning, and knowledge distillation techniques. The experimental results on the self-made dataset of surface defects on wind turbine blades indicate that the optimized model has a parameter count that is only 48.79% of the small version of the YOLOv5 model. However, its mean Average Precision (mAP) and frame rate have increased by 5.05% and 8.1 frames/s, respectively, reaching 94.56% and 43.7 frames/s. The lightweight algorithm proposed in this study meets the accuracy and real-time requirements for surface defect detection on wind turbine blades.

Using the Boundary Element Method for airfoil trailing edge noise prediction

This study investigates two aspects of the prediction of trailing edge noise from an airfoil using the Boundary Element Method to solve the scattering phenomenon. The first one consists in defining the surface pressure spectrum near the trailing edge as a source for the turbulent boundary layer-trailing edge interaction, using either an empirical model or one-dimensional turbulent boundary layer theory. The second aspect focuses on the capability of the Boundary Element Method to handle general boundary conditions. It is applied to predict the noise emitted by a porous trailing edge. This work is conducted in the context of aerodynamic noise from wind turbine blades, but has a wider range of engineering applications.

WIND power noise systematically underestimated in Sweden

This paper outlines a numerical study of measurement faults in regard to wind power turbines in Sweden. For this purpose, seven (7) reports of noise level from four (4) wind power stations, with between seven (7) and 47 on shore turbines, and between 145 m and 230 m high, were examined. Parallel studies were performed with analytic methods. Technically the noise level was undervalued by more than five (5) dB(A). The effect of the wind speed at 10 m height, according to the IEC64100-11 regulations, was generally not taken into account. In some cases, only the wind speed at the turbine hub was regarded. Thereby the correct wind speed at 10 m height was overstated by up to five (5) meters per second. In one case the measurement of wind power noise was measured at wind speed between three (3) and four (4) meters without the wind turbine blades moving at all. In summary the wind power noise levels were suppressed by about 5 dB(A) for the wind power stations analyzed in Sweden. The study results in a differentiated model as compared to the required rule in IEC64100-11. The projects were carried out between the years 2012 and 2024.

Experimental characterization of stall noise on a pitching airfoil in an anechoic wind tunnel

Dynamic stall noise is one of the potential source of amplitude modulations associated with wind turbine noise. This phenomenon is related to the periodic separation and reattachment of the boundary layer on the wind turbine blade suction side during its rotation. Within the framework of the PIBE project (Predicting the Impact of Wind Turbine Noise), experiments were conducted in an anechoic wind tunnel in order to characterize stall noise on a pitching airfoil in both static and dynamic conditions. A first set of measurements was performed using an airfoil equiped with pressure taps to measure both steady and unsteady wall pressure as well as far-field acoustic pressure. These measurements were used to identify the noise regimes associated with different angles of attack, and to relate them with the boundary layer evolution. In a second experiment, synchronized flow and acoustic measurements have been obtained to identify the coherent aerodynamic structures responsible for the noise radiation. The velocity fluctuations evaluated from the time-resolved particle image velocimetry (TR-PIV) data are correlated with acoustic pressure to localize aeroacoustic sources, and various tools such as vortex detection methods and spectral proper orthogonal decomposition are applied to identify the nature of these sources.

Innovations in Wind Turbine Blade Engineering: Exploring Materials, Sustainability, and Market Dynamics

This manuscript delves into the transformative advancements in wind turbine blade technology, emphasizing the integration of innovative materials, dynamic aerodynamic designs, and sustainable manufacturing practices. Through an exploration of the evolution from traditional materials to cutting-edge composites, the paper highlights how these developments significantly enhance the efficiency, durability, and environmental compatibility of wind turbines. Detailed case studies of notable global projects, such as the Hornsea Project One, the Gansu Wind Farm, and the Block Island Wind Farm, illustrate the practical applications of these technologies and their impact on energy production and sustainability. Additionally, the manuscript examines the critical role of regulatory frameworks and industry standards in fostering these technological advancements, ensuring safety, and promoting global adoption. By analyzing the current trends and future directions, this study underscores the potential of modern turbine technologies to meet the increasing global demand for renewable energy and contribute to sustainable development goals. The findings advocate for continued innovation and policy alignment to fully harness the potential of wind energy in the renewable energy landscape.

Techno‐Economic Analysis of Additively‐Manufactured Wind Turbine Blade Tips That Enable Technology Integration

ABSTRACTThe Additively‐Manufactured, System‐Integrated Tip (AMSIT) project is leveraging the flexibility of 3D printing to integrate several technologies in a wind turbine blade tip, while reducing the levelized cost of electricity (LCOE) produced. The design integration is demonstrated for a 200‐kW–scale turbine with 13‐m blades, with the outer 15% of the blade replaced with a 3D‐printed design. Aerodynamic performance is enhanced without increasing swept area through inclusion of a winglet and surface texturing, both challenging for traditional manufacturing. Longevity and durability are improved through integrated lightning and leading edge erosion protection. Increased power, reduced repair frequency, and ease of repair through blade modularity all contribute to reduced LCOE. The analysis is also extended to modern MW‐scale designs to estimate the impact of the technology at scale, demonstrating the potential to reduce LCOE significantly for modern onshore turbines, with even higher potential savings offshore.

Enhancing wind turbine blade protection: Solid particle erosion resistant ceramic oxides-reinforced epoxy coatings

Wind energy has been regarded as one of the renewable energy sources to rely on in the future. In this aspect, wind turbine blade maintenance is quite a challenge in tropical areas like India. One of the main reasons why wind turbine blades get damaged and produce less energy is solid particle erosion. In the present work, nanocomposite epoxy (EP) coatings reinforced with Al2O3, ZrO2, and CeO2 nanoparticle fillers have been applied on glass fiber reinforced polymer (GFRP) substrates using a simple spray coating method. These nanoparticles have been prepared in-house by solution combustion synthesis (SCS) route using urea, glycine, and oxalyl dihydrazide fuels. X-ray diffraction, field emission scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy have been used to characterize the materials and coatings. EP coatings with different Al2O3, ZrO2, and CeO2 nanoparticle concentrations have been subjected to solid particle erosion resistance tests at impinging angles of 30°, 60° and 90°. ZrO2 and CeO2 nanoparticle-reinforced EP coatings show better resistance to solid particle erosion than Al2O3-reinforced coatings. Estimated average erosion rates are 17 and 11.3 × 10−3 mm3 g−1, respectively, for epoxy coatings with 20 and 40 wt% ZrO2 nanoparticles. However, GFRP substrate and neat EP coating show much higher erosion rates with respect to nanoparticles-reinforced EP coatings. To ascertain a correlation between H3/E2 and the solid particle erosion rates of the coatings, nanoindentation tests have been carried out. Tensile strength and initial modulus of all the coatings are found to be directly proportional to the average erosion rates, whereas, elongation at break shows an inverse relationship with the average erosion rate. This correlation of mechanical properties with solid particle erosion performance can play a critical role in the development of realistic simulation of protective coatings for wind turbine blades.

Fault Diagnosis of Wind Turbine Blades with Continuous Wavelet Transform based Deep Learning Model Using Vibration Signal

Wind Turbines are the most crucial devices in wind energy conversion systems to increase energy generation efficiency from wind sources. Blade failure in wind turbines is due to the induced vibrations of change in ecological variables. It is necessary to periodically inspect the state of the wind turbine blades to enhance safety by decreasing downtime, lessening the likelihood of unplanned failures requiring extensive repair, and progressively increasing power generation with reduced logistical costs. The primary goal of the proposed research is to adopt a hybrid strategy that combines convolutional neural network models and continuous wavelet transform. The bump wavelet-based continuous wavelet transform with a convolutional neural network model is employed to classify the faulty wind turbine blades based on the extracted vibration signals of turbine blades. This approach distinguishes between different states of blade faults affecting wind turbine blades during operational phases. The research considers blade faults in the horizontal axis wind turbine, including blade bending, erosion, and the connection looseness between the hub and blade. The cross-validation and hold-out methods are used to validate the classification accuracy and are compared with other existing popular methods. The hold-out method has a better classification accuracy of 97.916%.

Design and analysis of hundred-meter wind turbine blade trailing edge based on finite element method (FEM)

Abstract The trailing edge region of composite wind turbine blades usually has a large deformation under wind load and the accidents caused by the damage of blade trailing edge accounts for a large proportion among blade accidents. With the development of large blade size, higher requirements are put forward for the stability of wind turbine blade trailing edge. Therefore, the trailing edge region is critical in the design of blade. A detailed study of the design and analysis for wind turbine blade trailing edge region was carried out in which the structure stability was regarded as the key. The influence of auxiliary spar cap and auxiliary spar web on the stiffness distribution and stability of the trailing edge were studied based on focus and finite element method (FEM). The respiratory effect of different structures due to deformation were analyzed and compared. The results showed that the structure of the auxiliary spar cap and auxiliary spar web can significantly increase stiffness, stability and decrease respiratory deformation at the trailing edge of blade compared to the traditional three webs structure. The structure of auxiliary spar and auxiliary spar web is the best design scheme for hundred-meter composite blade trailing edge.

Effects of sound on bluff body aerodynamic characteristics in separated and reattaching flows

The coupling effects between sound and flow on the aerodynamic characteristics of bluff bodies are commonly encountered in engineering practices, such as wind turbine blades and heat exchanger compressors. This study experimentally investigates the effects of sound over a broad range of frequencies (0–400 Hz) and sound pressure levels (80–105 dB) on the streamwise wind pressures on a flat plate in both smooth and turbulent flows. Spectral analysis and proper orthogonal decomposition (POD) are employed to explore the effects of sound on the aerodynamic forces acting on the flat plate. The results show that the effects of sound on wind pressure distributions and separation bubble behaviors over the flat plate depend on both sound frequency and sound pressure level. Furthermore, the findings highlight the role of acoustic resonance, which can increase the fluctuating wind pressure on the plate surface by over 400%. These effects can also be influenced by sound pressure levels. Additionally, the results demonstrate varying degrees and forms of attenuation of sound effects in turbulent flows, depending on the wind flow characteristics.

Optimization Design of Bionic Leading-edge Protuberances on Horizontal Axis Wind Turbine Blades

Abstract The complex operating environments of horizontal axis wind turbines has made the phenomenon of blade flow separation more obvious. As a passive flow control method, the bionic humpback whale leading-edge protuberances have been shown to effectively enhance the performance of the wind turbine. This study employs a multi-objective genetic algorithm and Computational Fluid Dynamics method to analyse the impact of leading-edge protuberances on the aerodynamic performance and flow characteristics of the blades. The results indicate a significant improvement in blade performance after optimization in the wind turbine’s output power. The streamwise vortices generated by the bionic protuberances not only reduce the suction surface pressure, but also suppress the spanwise flow over the blade surface. The length of the flow separation Region is reduced from 0.410 to 0.368 radius. In the process of wind speed change, the tangential forces on the bionic blade exhibit a wave-like variation. The bionic protuberance alters the pressure coefficient of the position. Compared with the original blade, the pressure coefficient of the trough sections on both sides of the bionic blade protuberance is improved. In this study, the bionic protuberance applied to the leading-edge of horizontal-axis wind turbine blades is proposed for the first time, and holds practical value for guiding practical applications.

Stability impact on wind turbine blades trailing edge from bonding zone modelling methods

Abstract The trailing edge of wind turbine blade will undergo a large deformation under the action of load, resulting in a higher risk of damage and failure. The finite element analysis modeling method directly affects the simulation result, furthermore impacts the result of blade structure design. Therefore, it is necessary to find out a modeling method, which is capable to reflect the stability of bonding regions more accurately. This paper aims to discuss the influences of different finite element modeling methods on the buckling stability of blade trailing edge. The influences of shell element, tetrahedron element and hexahedron element on the blade stiffness are considered. The bonding region were simulated separately by combining shell element with bonding web, shell element with tetrahedron element and shell element with hexahedron. The influences of different bonding region modeling methods on the trailing edge buckling factor were analyzed by using the eigenvalue buckling analysis method of finite element. The simulation results provided data support for the future validation of the blade trailing edge bonding area modeling method. The results show that, the tetrahedral mesh provides a higher stiffness, followed by the hexahedral mesh, and the adhesive web form has the smallest stiffness. In order to simulate the more realistic stiffness of the adhesive area at the trailing edge of the blade, adhesive web plates can be built in the flange area of the blade root and the core material area of the trial adhesive mold; The direct bonding area can be simulated employing the hexahedron mesh; The tetrahedral mesh has high stiffness and is not suitable for modeling the adhesive area at the trailing edge. Blade simulation modeling can flexibly use different adhesive forms according to actual situations, ensuring the reliability of the simulation model.

Analysis of vortex induced vibration on the hundred-meter wind turbine blade based on CFD and FEM

Abstract Along the development of wind turbine blade toward large size and light weight, the length of blade running-now has come to the level of hundred-meter, while the structure of blade trends to be flexible. During the shutdown conditions, blades are affected by wake vortex from different inflow speed and angle, which often induce blade vibration. It seriously affects the safety and service life of wind turbines, even may cause blade breakage accident. This paper focused on the vortex induced vibration on the hundred-meter wind turbine blade. Based on the Computational Fluid Dynamics (CFD) transient method, the wake flow field of three relative thickness aerofoils has been simulated under different inflow speed and angle. The distribution of vorticity has been compared. Based on the Fast Fourier Transform (FFT) method, the frequency of wake vortex has been analysed from the pressure pulsation, compared with the natural frequency of this hundred-meter blade calculated by the Finite Element Method (FEM). This result may be regarded as a simulation support to avoid vortex induced vibration of hundred-meter wind turbine blade.

Facilitating water droplet removal from surfaces using air flow and wettability gradients

A new method is proposed to mitigate ice accretions on wind turbine blades via the creation of a microstructural gradient surface geometry that facilitates spontaneous water droplet motion along the surface. The wettability gradients are formed by laser etching 35 μm wide, 35 μm deep channels into aluminum to form a surface with a gradually increasing solid area fraction. Different design variations are then proposed and systematically evaluated on the merits of their performance. An analytical model is also derived based on a balance of hysteresis and drag forces to predict the critical airspeed necessary for droplet movement as a function of the droplet size and surface contact angle. Experimentation has shown good agreement with the model for both the baseline and fixed-pitch channel surfaces and has also demonstrated that, in certain cases, up to 70 % lower critical airspeeds are needed to initiate droplet motion on these microstructured surfaces.

Cure-induced residual stresses and viscoelastic effects in repaired wind turbine blades: Analytical-numerical investigation

During scarf repair of wind turbine blades, the difference in coefficients of thermal expansion and chemical shrinkage between the original part and the repair patch leads to the development of residual stresses. These residual stresses are detrimental when the repaired composite structures are subjected to operational cyclic loads and affect their post-repair lifetime. This paper uses a hybrid analytical-numerical model to evaluate the residual stresses in a scarf-repaired composite panel. A Prony series-based viscoelastic model is used to describe the material behaviour of the composite undergoing cure to replicate real-life effects more closely. Experiments on the repaired composite samples and numerical simulations on a model of the same are performed to study the post-repair mechanical behaviour. It is found that the damage initiates at the adhesive interface between the scarf patch and the base composite. The resulting debonding and damage to the base composite leads to the failure of the repaired section.

Research on wind turbine icing prediction data processing and accuracy of machine learning algorithm

Studying the icing problem of wind turbine blades is crucial for optimizing wind farm operation and maintenance. Traditional machine learning algorithms like Random Forest and Support Vector Machines have limitations in handling complex time series data and capturing long-term dependencies, leading to insufficient accuracy and generalization. To address these gaps, this paper proposes a comprehensive approach involving advanced machine learning frameworks and feature engineering techniques. This paper based on the original SACDA dataset, four distinct types of processing are performed on the prediction data via PCA dimensionality reduction and the introduction of new features; meanwhile, the four types mentioned above of datasets are trained and predicted using the Gated Recycling Unit model (GRU), Random Forest (RF), GA-BP Neural Network (BP), and Extreme Learning Machine (ELM) models. The results indicate that the prediction accuracies of all four types of models are more satisfactory, with the RF model having the highest prediction accuracy and the overall accuracy remaining above 99 percent, the dataset + RF model after dimensionality reduction of the original sensitive features having the highest prediction accuracy and speed.

Synthesis of SiC nanowires from retired wind turbine blades and their microwave-absorbing property

Retired wind turbine blades (RWTBs) mainly consist of glass fibers and resins, which have abundant of carbon and silicon resources. This study synthesized SiC nanowires (SiC NWs) by using the RWTBs for the first time. The RWTBs were grinded into powders and pyrolyzed at 600 °C for 2 h, the pyrolysis solid residues (P-RWTBs) mixed with apricot shell char (ASC) and silicon powder in a stoichiometric ratio (C/Si=4), and then the mixture calcined at 1550 °C for 4 h in an argon atmosphere. XRD, FTIR and XPS results indicating that SiC NWs had been successfully synthesized. SEM and TEM micrographs show that the produced SiC NWs exhibit a worm-like shape, with diameters of 50–100 nm, and interweave into a 3D network body. The minimum reflection loss (RLmin) of the SiC NWs 3D network body reached -18.17 dB at the thickness of 4.8 mm, which meet the requirements of microwave-absorbing materials. Its good microwave-absorption property is due to the various loss types of the electromagnetic waves that caused by the special structure. This study provides a new approach for high-value utilization of the RWTBs, which is of great significance in realizing the "green retirement" of glass fiber reinforced polymers.

Assessing wind turbine blade durability longevity utilizing national renewable energy laboratory tools

With the escalating significance of renewable energy, there exists a pressing demand for precise software and tools capable of designing and forecasting wind turbine blade service life. OpenFAST, TurbSim, and MLife are pivotal open-source wind turbine simulation tools that integrate aerodynamics, structural dynamics, wind simulation, and control systems. They enable accurate prediction of wind turbine performance. This study aims to leverage these software resources to model turbulent wind conditions using predefined basic parameters and then calculate fatigue and longevity of the wind turbine blade to determine service life. Particularly, MLife was employed for rose loading, enhancing the fidelity of the loading cycle simulation. Collaboration between the National Renewable Energy Laboratory and the research team played a crucial role in establishing a foundational baseline and implementing realistic input parameters for evaluating the ultimate load, determining damage equivalent loads (DEL), and projecting service life. In all simulations, a constant factor of safety (FOS) of 1.5 was consistently applied. Additionally, Finite Element Analysis (FEA) was employed to validate our numerical experiments, ensuring the accuracy of the obtained results by correlating simulation outcomes with real-world scenarios, further strengthening the credibility of the study.