Large-scale Wind Turbine Blade Research Articles

Numerical Analysis of Leading-Edge Roughness Effects on the Aerodynamic Performance of a Thick Wind Turbine Airfoil

The aerodynamic performance of wind turbine airfoils is crucial for the efficiency and reliability of wind energy systems, with leading-edge roughness significantly impacting blade performance. This study conducts numerical simulations on the DU 00-W-401 airfoil to investigate the effects of leading-edge roughness. Results reveal that the rough airfoil exhibits a distinctive “N”-shaped lift coefficient curve. The formation mechanism of this nonlinear lift curve is primarily attributed to the development of the trailing-edge separation vortex and variations in the adverse pressure gradient from the maximum thickness position to the trailing-edge confluence. The impact of different roughness heights is further investigated. It is discovered that when the roughness height is higher than 0.3 mm, the boundary layer can be considered fully turbulent, and the lift curve shows the “N” shape stably. When the roughness height is between 0.07 mm and 0.1 mm, a transitional state can be observed, with several saltation points in the lift curve. The main characteristics of different flow regimes based on different lift curve segments are summarized. This research enhances the understanding of the effects of leading-edge roughness on the aerodynamic performance of a thick wind turbine airfoil, and the simulation method for considering the effect of leading-edge roughness is practical to be applied on large-scale wind turbine blade to estimate the aerodynamic performance under rough leading-edge conditions, thereby supporting advancements in wind turbine technology and promoting the broader adoption of renewable energy.

Performance and application of pultrusion-processed fibre-reinforced composites in large-scale wind turbine blades

Pultruded composite materials have broad application prospects in the field of wind power generation. In this study, we explored the application of three different pultruded composites for the spar caps of wind turbine blades. Through comprehensive morphological, thermal, and mechanical analyses, as well as static and fatigue loading tests, we assessed the properties of these composites. Notably, the pultruded composites demonstrated high modulus, adequate strength, and excellent fatigue resistance. Among them, the optimal composite had an elastic modulus that was 46.4% higher than that of an E-glass vacuum-assisted resin-infused laminate. To further investigate their viability, we constructed a finite element model for a wind turbine blade with a pultruded composite spar cap using ANSYS. The results indicated that in a 94-m blade, replacing the E-glass vacuum-assisted resin-infused blade spar cap with the pultruded composite would result in a substantial 32.5% weight reduction. Finally, a 94-m blade was prototyped and tested, confirming its compliance with static and fatigue loading requirements. This study contributes to the advancement of composite materials and manufacturing methods for large-scale wind turbine blades.

The wind tunnel test research on the aerodynamic stability of wind turbine airfoils

The issue of nonlinear aerodynamic stability of blades is a significant technological bottleneck in the development of large-scale wind turbines. In order to explore the influencing parameters and mechanisms of the nonlinear aerodynamic stability of large-scale wind turbine blades, the flexible blade was simplified into a two-dimensional rigid blade segment with elastic supports, which formed the pitch single-degree-of-freedom aeroelastic wind tunnel test system. Through wind tunnel vibration and pressure measurement synchronization tests, the torsional vibration characteristics and the flow field development mechanism of the airfoil under different wind speeds and attack angles were studied in detail. The wind tunnel tests revealed two distinct torsional aeroelastic behaviors: the static equilibrium state with negligible amplitude and high vibrational randomness, and the stall flutter state with larger amplitude, which was changed according to sinusoidal law substantially. The stall flutter state was confined within a specific wind speed range, and its stability boundary, which included the critical initiation wind speed and the critical cessation wind speed, all varied linearly with the installation attack angle. The growth rate of the critical cessation wind speed with the installation attack angle was significantly higher than that of the critical initiation wind speed, making the wind speed range for the occurrence of stall flutter also linearly larger. Additionally, the frequency of the stall flutter was significantly higher than the natural frequency of the model, and it exhibited a positive correlation with the critical initiation wind speed. The flow state around the airfoil during stall flutter was primarily distinguished from its static counterpart by the presence of leading-edge vortices. The formation and shedding of these leading-edge vortices would significantly influence the characteristics of stall flutter.

Development and Application of Medium-reactivity Epoxy Infusion Resin System in Large-scale Wind Turbine Blades

In view of the requirement of cost reduction and efficiency increase for large-scale wind turbine blades, a medium-reactivity epoxy infusion resin system was developed, which contained 20% fast curing agent and 80% slow curing agent. The properties of medium-reactivity epoxy infusion resin system were evaluated via physical and chemical analysis, application process ability analysis, resin clear casting mechanical properties analysis, and laminate specimens mechanical properties analysis. The results indicated that the mechanical properties of this medium-reactivity epoxy infusion resin system can meet the requirements of blade design, and the pre-curing time of the resin was reduced from 3.0h to 2.3h. The application process ability of medium-reactivity epoxy infusion resin system in large-scale wind turbine blade was also verified. The blade parts pre-curing time was shortened by 0.5-1 hour, which meets the target of blade cost reduction and efficiency increase.

Anomaly Detection on Small Wind Turbine Blades Using Deep Learning Algorithms

Wind turbine blade maintenance is expensive, dangerous, time-consuming, and prone to misdiagnosis. A potential solution to aid preventative maintenance is using deep learning and drones for inspection and early fault detection. In this research, five base deep learning architectures are investigated for anomaly detection on wind turbine blades, including Xception, Resnet-50, AlexNet, and VGG-19, along with a custom convolutional neural network. For further analysis, transfer learning approaches were also proposed and developed, utilizing these architectures as the feature extraction layers. In order to investigate model performance, a new dataset containing 6000 RGB images was created, making use of indoor and outdoor images of a small wind turbine with healthy and damaged blades. Each model was tuned using different layers, image augmentations, and hyperparameter tuning to achieve optimal performance. The results showed that the proposed Transfer Xception outperformed other architectures by attaining 99.92% accuracy on the test data of this dataset. Furthermore, the performance of the investigated models was compared on a dataset containing faulty and healthy images of large-scale wind turbine blades. In this case, our results indicated that the best-performing model was also the proposed Transfer Xception, which achieved 100% accuracy on the test data. These accuracies show promising results in the adoption of machine learning for wind turbine blade fault identification.

Concept and Life Cycle Assessment of a Tiny House Made from Root Section Structures of a Decommissioned Large-Scale Wind Turbine Blade as a Repurposed Application

With the green energy transition, the wind industry has grown rapidly in recent decades. Wind turbine blades (WTBs) are primarily manufactured from glass fibers and thermoset matrix composites. Considering their lifetime from 20 to 25 years, significant amounts of wind turbine components will eventually enter the global waste stream. Currently, recycling is not sufficiently optimized and commercially available. Other strategies, such as repurpose, are becoming relevant to divert components from waste streams. This research explores a pathway to sustainable repurposing of decommissioned WTBs. The concept of a tiny house constructed from the root section of a 5 MW/61.5 m WTB is presented (“5 MW house”). The deformations and stresses of the repurposed composite structures were investigated using a finite element analysis based on the three load cases, defined by (1) a combination of snow load and payload, (2) a combination of wind load and payload, and (3) a thermal stress analysis of a critical temperature distribution of the 5 MW house. Furthermore, a life cycle assessment (LCA) was conducted to evaluate the environmental impacts of the proposed concept. The numerical analysis results showed that the 5 MW house can withstand the applied loads, and that the deformations are within acceptable limits. A reduction of up to 97% in environmental impacts for most impact categories was calculated, compared to a wooden tiny house, whereas climate change, ozone depletion, and eutrophication potential were up to 3.7 times higher, mainly due to the weight and composition of the 5 MW house. The authors believe that the proposed concept may be a high-volume repurposed solution for large-scale WTB root sections.

Optimal airfoil selection for small horizontal axis wind turbine blades: A multi-criteria approach

Over the last century, the growing demand for clean energy has emphasized wind energy as a promising solu-tion to address contemporary energy challenges. Within the realm of wind energy, the wind turbine plays a pivotal role in harnessing the kinetic energy of the wind and converting it into electrical power. Among the various components of the wind turbine system, turbine blades assume a critical role in capturing the wind's kinetic energy and converting it into rotational motion. Consequently, the design of wind turbine blades holds the utmost importance in determining the overall performance and efficiency of the entire wind turbine system. One essential aspect of blade design involves selecting an appropriate airfoil. Throughout history, numerous airfoil profiles have been developed for various applications. Notably, National Advisory Committee for Aeronautics (NACA) and National Renewable Energy Laboratory (NREL) airfoils have been tailored for aircraft and large-scale wind turbine blades, respectively. However, the quest for suitable airfoil types for small-scale wind turbine blades has been ongoing. This study delves into an examination of over 62 distinct NACA and NREL aerofoil types tailored for small horizontal-axis wind turbine blades. Employing specialized software, namely QBlade, specifically designed for modeling and simulating wind turbine blades, the study calculates key parameters such as power output, stress, deformation, and weight for each airfoil. Subsequently, based on the simulated data, the optimal airfoil is identified using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria selection approach. This selection process takes into account simulation results pertaining to power output, stress, deformation, and weight. The decision-making process involving multiple criteria is facilitated using Excel and Python. The findings of this study reveal that among the 62 airfoil types under consideration, the NACA 0024, NACA 2424, and NACA 4424 airfoils emerge as the most suitable choices for small horizontal-axis wind turbine blades.

Identification of Damage in a Wind Turbine Blade Using Mechanical Measurements and Artificial Neural Networks

Due to the stochastic nature of environmental loadings, a lot of interest is paid in the discovery of possible damages of the involved equipment in modern industry. In wind turbines’ blades, the development of a smart structural health monitoring system is essential. In this paper, a large-scale composite wind turbine blade model is designed and used for the detection of several damage scenarios. The process is mainly based on the development of monitoring techniques which exploit the capabilities of artificial neural networks. These techniques can provide the exact position of possible damages, under given external loading scenarios. Moreover, the use of such methods decreases significantly the need of external intervention and at the same time it increases the accuracy of the whole approach. The above processes are simulated using the finite element method. The goal is to develop a neural network which realizes the correlation of measurements with damage patterns. The goal is focused on the solution of inverse problems involving elastically deformable structures, based on remote mechanical measurements. The correlation between measurements and damages, which is much more complicated in comparison to image analysis, is studied by means of neural networks.

Mitigation of In-Plane Vibrations in Large-Scale Wind Turbine Blades with a Track Tuned Mass Damper

To mitigate in-plane vibrations of wind turbine blades, a track tuned mass damper (TMD) is proposed and its performance for mitigating blade in-plane vibration is investigated considering various influence factors. Firstly, the organization and operational principles of the damping control device are explained. Then, the equations of motion of the individual TMD-equipped blade are then deduced from Euler–Lagrange. Secondly, blade’s wind loading is calculated by blade element momentum theory considering the blade rotation effect through the rotating sample spectrum. Thirdly, the dynamical response of the blade based on the MATLAB/SIMULINK tool is calculated. The peak maximum displacement and standard deviation of the blade tip are chosen as the estimation indicators to assess the TMD’s effectiveness of the device considering actually various argument including mass ratio μ , damping ratio ξ , and installation position x 0 / L . Based on the assumption that the mass block in the vibration reduction control device has no contact with the inside surface of the blade web in operation, the optimal relative values of mass ratio, damping ratio, and installation position of a single blade are determined as 0.03, 15%, and 0.55, respectively. As a result, the reduction of the peak value and the standard deviation can reach 52.78% and 53.75%, respectively. Therefore, with the optimal parameters, the designed vibration control device effectively not only reduces the blade tip displacement but also avoids the damage due to in-plane vibrations.

Accurate identification of cross-sectional bending stiffness in large-scale wind turbine blades through static loading test

To ensure the safe and stable operation of wind turbines, it is essential that the blades have sufficient bending stiffness to prevent excessive deflection and tower impact. A method combining static loading test and numerical analysis is proposed to solve the problem of identifying the cross-sectional bending stiffness of actual blades. Two working conditions, namely multi-point static test and single-point static calibration, are considered. A mathematical model of a cantilever beam with an initial small curvature and variable cross section is established. By fitting the deflection measurement data obtained from the static loading test, the deflection differential equation is solved by the finite difference method to obtain expressions for the cross-sectional bending stiffness under large and small deflection. The analysis results of several blade models show that the bending stiffness identification error for most blade sections is less than 10%, confirming the effectiveness of this method. This provides a practical and theoretical basis for the design, analysis, and refinement of test parameters for large-scale blades.

Aerodynamic load evaluation of leading edge and trailing edge windward states of large-scale wind turbine blade under parked condition

The safety and reliability of wind turbine blades are increasingly challenged by extreme wind conditions such as typhoons, as wind turbines tend to become larger. Under these conditions, most units will be shut down and the blades will be pitched to around 90° to minimize the loads. This paper aims to compare a new strategy for the parked condition, i.e., the trailing edge windward state, with the traditional leading edge windward state to verify its technical feasibility. The aerodynamic loads of a 30%-thickness airfoil and a commercial wind turbine blade are comprehensively evaluated by wind tunnel experiment, CFD simulation and engineering analytical model. The two-dimensional airfoil cases indicate that the airfoil resultant force is lower in the trailing edge windward state than in the leading edge windward state for a wide range of angles of attack. Consequently, the three-dimensional blade cases shows that the low load region of the trailing edge windward state is relatively wider than that of the leading edge windward state. The averaged blade root load is reduced by 41.4% ~ 57.8% through trailing edge windward state with prescribed error bounds of windward angular. Besides, it is suggested that the traditional engineering analytical model should improve the precision of the extrapolated airfoil data around AOA = 180 deg. to ensure the accurate load evaluation under the trailing edge windward state. This study suggests a new control strategy for wind turbine blades under the parked condition, which offers significant benefits for load reduction and has a good potential for future applications.

Aerodynamic design of wind turbine blade with second derivative of thickness distribution as constraint

In order to make more use of wind energy, large-scale wind turbine blade size is the trend of development. With the increasing of blade length, the design and manufacture of the structure with the requirements of safety and economy are faced with great challenges. It is most sensitive to the blade manufacturer to reduce the composite lamination and production cost as long as the stress and strain level of the structure is satisfied. Therefore, the ideal thickness distribution requires not only the thickness monotonically decrease along the radial direction, but also the concavity and convexity of the thickness distribution function are required to be constant. Based on the in-house design code SurroOpt and the momentum-blade theory method, an optimization design platform for wind turbine blades was established. A 400kW wind turbine blade design was carried out with the aim of maximizing the output power and the constraint of the second derivative of the thickness distribution. The results show that the concave-convex characteristic of thickness distribution function has not changed, which is beneficial to the structural design. The designed blades have been manufactured and installed for operation. For the whole device, the maximum coefficient of wind energy utilization (including the loss of motor and machinery) reaches 0.42, which is 2.4% higher than 0.41 of the same kind of products.

Carbon Fiber Composites for Large-Scale Wind Turbine Blades: Applicability Study and Comprehensive Evaluation in China

Wind energy is a type of clean energy that can address global energy shortages and environmental issues. Wind turbine blades are a critical component in capturing wind energy. Carbon fiber composites have been widely recognized for their excellent overall performance in large-scale wind turbine blades. However, in China, the wide application of carbon fiber composites in wind turbine blades still faces many problems and challenges. This paper examines the current state of carbon fiber composites for wind turbine blades and the geographical distribution characteristics of wind resources in China. The economic revenues from increasing the length of wind turbine blades in four typical wind farms, including offshore wind farms, are compared. Using a mathematical model, the energy efficiency of carbon fiber composites in the application of large wind turbine blades is evaluated from the aspects of cost, embedded energy, and carbon footprint. Further, the current relationship between supply and demand for the industrial structure of carbon fiber in China is revealed. The manufacturing technologies for carbon fiber composite wind turbine blades are analyzed, and corresponding countermeasures are proposed. Finally, the incentive policy for applying carbon fiber composites to wind turbine blades is explained, and the development prospects are explored. In this paper, the economics and energy efficiency of the application of carbon fiber composite materials in large wind turbine blades are analyzed and comprehensively evaluated by using mathematical models, which will provide a valuable reference for China’s wind turbine blade industry.

Examining adequacy of the empirical Theodorsen function for wind turbine blade section-model aeroelasticity

The ability to reproduce aeroelastic loads of horizontal-axis wind turbine blade cross sections by Theodorsen function, currently employed by researchers and practitioners, is investigated. Section model experiments are conducted on two reduced-scale models of airfoil sections, derived from a benchmark large-scale wind turbine blade. Uncertainties associated with aeroelastic properties of the wind turbine blade sections, measured in the wind tunnel, are also examined. Uncertainties are associated with random, experimental laboratory errors. Statistical inference is utilized to characterize experimental errors. The results suggest that the Theodorsen function cannot be used while empirical aeroelastic coefficients (Scanlan derivatives), dependent on the cross-section geometry, are necessary. Furthermore, experimental errors, aptly quantified in this study, should be incorporated and included in reliability analyses of wind turbine blades.

Defect detection of large wind turbine blades based on image stitching and improved Unet network

Aiming at the problem that the existing computer vision detection technology is difficult to comprehensively and carefully detect the damage status of large wind turbine blades due to the limitation of the field of view, this paper proposes a refined and multi-scale detection method for large-scale wind turbine blades by combining an image stitching algorithm and a deep learning network. First of all, combining the image stitching algorithm with image weighted fusion, images of large wind turbine blades shot in close range are stitched together, so as to realize the clear restoration of the full size and defects of the blades. On this basis, an improved Unet network VGG16Unet is proposed. Combined with transfer learning, the classification and detection of various defects on wind turbine blades under the condition of small dataset training are realized. Finally, by the aid of the combination of the image stitching algorithm and the semantic segmentation network, the refined damage detection of the overall structure of large wind turbine blades is implemented. The research shows that the mean pixel accuracy and the mean intersection over union of the VGG16Unet model are 95.33% and 85.20%, respectively, which is better than the classical semantic segmentation models, fully convolutional neural network model and Unet model. The combination of the VGG16Unet model and the image stitching algorithm not only realizes the global detection of the entire structure but also ensures the detailed detection of each local area, which makes the detection of large wind turbine blades more comprehensive and refined.

Research on control methods and technology for reduction of large-scale wind turbine blade vibration

This paper is mainly devoted to the analysis and suppression of large-scale wind turbine blade vibration. Firstly, the mechanism of blade vibration including waved vibration and shimmy vibration is analyzed in detail and the mathematical model of blade vibration is established. Secondly, the influence of tower shadow effect and wind shear on blade flutter is discussed based on the established blade vibration model. In the end, for the suppression of blade vibration, some control schemes based on individual variable-pitch including blade damping control, LQG control, H∞ control and improved LQG control with optimal disturbance observer proposed in this paper are studied. At the same time, the specific processes of controllers design are given and these algorithms are effectively verified by simulations. The results show that the improved LQG control with optimal disturbance observer has the better suppression effect on blade vibration compared with other methods, which can provide a certain theoretical support to choose the control algorithm in reality.

Vibration Control of Large Wind Turbine Blades with Unidirectional Cable Pendulum Damper

A unidirectional cable pendulum damper is proposed to mitigate vibration responses of large-scale wind turbine blades in the edgewise direction, and the effectiveness of the proposed device for vibration response control is investigated. First, the configuration and working principles of the vibration damper are introduced. Second, the Euler–Lagrange equation of the single blade vibration damping system with the vibration damper is derived based on the Hamilton’s principle. At last, considering the effect of blade rotation, the wind load that applied on the blade was calculated using the rotating sample spectrum. The dynamic responses of blades are also calculated using the MATLAB/Simulink platform. The peak value and standard deviation of blade responses were taken as evaluation indexes to evaluate the vibration control efficiency of the device with varying the parameters such as the mass ball pendulum length, the fixed pulley block installation position, the stiffness and the pre-stress of the flexible cable. The optimal parameters of the vibration damper are investigated and obtained based on the assumption that no pounding happens between the mass ball of the vibration damper and the inner wall of the blade. Results show that the length of the mass ball pendulum and the installation position of the fixed pulley block, the values of which are within a reasonable range, can ensure the optimal performance of the vibration damper. The displacement of the mass sphere can be effectively reduced by increasing the stiffness of the flexible cable, and the pre-stress shows marginal beneficial effect on the damping performance and the displacement control of the mass sphere. Using the optimum parameters, the vibration damper can keep the mass ball within a safe running distance. The reduction of the peak value and the standard deviation of the blade displacement can reach 89.36% and 89.83%, respectively. The proposed device space can effectively reduce the blade tip response of the wind turbine by occupying less space. Moreover, the size of the device installation space can be changed by adjusting the weight ball swing length, which is suitable for the vibration control of the wind turbine blade edgewise direction.

Topology Optimization-Driven Design for Offshore Composite Wind Turbine Blades

With the increase in wind turbine power, the size of the blades is significantly increasing to over 100 m. It is becoming more and more important to optimize the design for the internal layout of large-scale offshore composite wind turbine blades to meet the structural safety requirements while improving the blade power generation efficiency and achieving light weight. In this work, the full-scale internal layout of an NREL 5 MW offshore composite wind turbine blade is elaborately designed via the topology optimization method. The aerodynamic wind loads of the blades were first simulated based on the computational fluid dynamics. Afterwards, the variable density topology optimization method was adopted to perform the internal structure design of the blade. Then, the first and second generation multi-web internal layouts of the blade were reversely designed and evaluated in accordance with the stress level, maximum displacement of blade tip and fatigue life. In contrast with the reference blade, the overall weight of the optimized blade was reduced by 9.88% with the requirements of stress and fatigue life, indicating a better power efficiency. Finally, the vibration modal and full life cycle of the designed blade were analyzed. The design conception and new architecture could be useful for the improvement of advanced wind turbines.

Effect of Spar Design Optimization on the Mass and Cost of a Large-Scale Composite Wind Turbine Blade

Mass and cost tradeoffs by deploying three optimized spars, made of all-glass, hybrid and all-carbon composites, applied to a publicly available large-scale composite blade of 100 m in length for a 13.2 MW wind turbine, are explored. The blade mass and cost minimizations are calculated for two design load cases, generating the worst aerodynamic loads for parked and rotating rotor blades, while meeting the stiffness, strength, stability and resonance design requirements, as recommended by the wind turbine standards. The optimization cases are formulated as a single-objective, multi-constraint optimization problem, while taking into account the manufacturability of hybrid spars in particular, and it is solved using a genetic algorithm method. The blade mass lowers in the range of 8.1–13.3%, 18.5–20.7% and 25.7–26.4% for the optimized all-glass, hybrid and all-carbon spars, respectively, while the cost decreases for the optimized all-glass spars only. The cost increases in a range of 1.2–13.6% and 24.5–31.5% when the optimized hybrid and all-carbon spars are used. Further, the hybrid spar optimization using the blade mass and cost objective functions, as well as the effects of spar optimization on the blade’s structural performance in terms of tip deflection, strength, buckling resistance and first natural frequency, are discussed.

Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

Abstract. As the wind energy industry is maturing and wind turbines are becoming larger, there is an increasing need for cost-effective monitoring and data analysis solutions to understand the complex aerodynamic and acoustic behaviour of the flexible blades. Published measurements on operating rotor blades in real conditions are very scarce due to the complexity of the installation and use of measurement systems. However, recent developments in electronics, wireless communication and MEMS (micro-electromechanical systems) sensors are making it possible to acquire data in a cost-effective and energy-efficient way. In this work, therefore, a cost-effective MEMS-based aerodynamic and acoustic wireless measurement system that is thin, non-intrusive, easy to install, low power and self-sustaining is designed and tested in a wind tunnel. The measurement system does not require an electrical connection to the wind turbine and can be mounted and removed without damaging the blade.The results show that the system is capable of delivering relevant results continuously, although work needs to be done on calibrating and correcting the pressure signals as well as on refining the concept for the attachment sleeve for weather protection in the field. Finally, two methods for using the measurements to provide added value to the wind energy industry are developed and demonstrated: (1) inferring the local angle of attack via stagnation point detection using differential pressure sensors near the leading edge and (2) detecting and classifying leading edge erosion using instantaneous snapshots of the measured pressure fields. Ongoing work involves field tests on a 6 kW operating wind turbine in Switzerland.