MW Horizontal Axis Wind Turbine Research Articles

Research on Aerodynamic Characteristics of Three Offshore Wind Turbines Based on Large Eddy Simulation and Actuator Line Model

Investigating the aerodynamic performance and wake characteristics of wind farms under different levels of wake effects is crucial for optimizing wind farm layouts and improving power generation efficiency. The Large Eddy Simulation (LES)–actuator line model (ALM) method is widely used to predict the power generation efficiency of wind farms composed of multiple turbines. This study employs the LES-ALM method to numerically investigate the aerodynamic performance and wake characteristics of a single NREL 5 MW horizontal-axis wind turbine and three such turbines under different wake interaction conditions. For the single turbine case, the results obtained using the LES-ALM method were compared with the existing literature, showing good agreement and confirming its reliability for single turbine scenarios. For the three-turbine wake field problem, considering the aerodynamic performance differences under three cases, the results indicate that spacing has a minor impact on the power coefficient and thrust coefficient of the middle turbine but a significant impact on the downstream turbine. For staggered three-turbine arrangements, unilateral turbulent inflow to the downstream turbine causes significant fluctuations in thrust and torque, while bilateral turbulent inflow leads to more stable thrust and torque. The presence of two upstream turbines causes an acceleration effect at the inflow region of the downstream single turbine, significantly increasing its power coefficient. The findings of this study can provide methodological references for reducing wake effects and optimizing the layout of wind farms.

Enhanced Analysis of Ice Accretion on Rotating Blades of Horizontal-Axis Wind Turbines Using Advanced 3D Scanning Technology

This study investigated the meteorological conditions leading to ice formation on wind turbines in a coastal mountainous area. An enhanced ice formation similarity criterion was developed for the experimental design, utilizing a scaled-down model of a 1.5 MW horizontal-axis wind turbine in icing wind tunnel tests. Three-dimensional ice shapes on the rotating blades were obtained and scanned using advanced 3D laser measurement technology. Post-processing of the scanned data facilitated the construction of solid models of the ice-covered blades. This study analyzed the maximum ice thickness, ice-covered area, and dimensionless parameters such as the maximum dimensionless ice thickness and dimensionless ice-covered area along the blade. Under the experimental conditions, the maximum ice thickness reached 0.5102 m, and the ice-covered area extended up to 0.5549 m2. The dimensionless maximum ice thickness and dimensionless ice-covered area consistently increased along the blade direction. Our analysis of 3D ice shape characteristics and the ice volume under different test conditions demonstrated that wind speed and the liquid water content (LWC) are critical factors affecting ice formation on blade surfaces. For a constant tip speed ratio, higher wind speeds and a greater LWC resulted in increased ice volumes on the blade surfaces. Specifically, increasing the wind speed can augment the ice volume by up to 57.2%, while increasing the LWC can enhance the ice volume by up to 149.2% under the experimental conditions selected in this study.

Multidimensional hybrid software-in-the-loop modeling approach for experimental analysis of a floating offshore wind turbine in wave tank experiments

A hybrid experimental modeling approach for floating offshore wind turbines (FOWTs) in a wave tank is presented. The method called real-time hybrid method (RTHM) or software-in-the-loop (SIL) includes physically reproduced hydrodynamic loads in the wave tank, with a Froude-scaled model while aerodynamic loads are reproduced on the model by an actuator. The force is applied on the tower top and calculated by a numerical simulation running in real-time as a function of the measured velocity and position of the physical model. Couplings between the platform motion, the aerodynamic loads and the wind turbine controller are hence accounted for. A new SIL actuator enabling the reproduction of a multi-component force at the tower top of an experimental scaled wind turbine model is developed, and the quantification of the accuracy of the replicated forces is studied. The test case includes a floating spar platform carrying a 10 MW horizontal axis wind turbine. The results show that this SIL actuator can accurately replicate the low and wave-frequency aerodynamic loads, which are essential for wave tank testing. Lastly, a case study of the wind turbine model in colinear and misaligned wind and wave conditions is presented, showing 3D forces and induced motions.

OC6 project Phase IV: validation of numerical models for novel floating offshore wind support structures

Abstract. This paper provides a summary of the work done within Phase IV of the Offshore Code Comparison Collaboration, Continued with Correlation and unCertainty (OC6) project, under International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the loading on and motion of a novel floating offshore wind system. Numerical models of a 3.6 MW horizontal-axis wind turbine atop the TetraSpar floating support structure were compared using measurement data from a 1:43-Froude-scale test performed in the University of Maine's Alfond Wind–Wave (W2) Ocean Engineering Laboratory. Participants in the project ran a series of simulations, including system equilibrium, surge offsets, free-decay tests, wind-only conditions, wave-only conditions, and a combination of wind and wave conditions. Validation of the models was performed by comparing the aerodynamic loading, floating support structure motion, tower base loading, mooring line tensions, and keel line tensions. The results show a relatively good estimation of the aerodynamic loading and a reasonable estimation of the platform motion and tower base fore–aft bending moment. However, there is a significant dispersion in the dynamic loading for the upwind mooring line. Very good agreement was observed between most of the numerical models and the experiment for the keel line tensions.

Robust control of wind turbines to reduce wind power fluctuation

AbstractThe wind power generation system of a 5 MW horizontal axis wind turbine has a high wind energy conversion efficiency. The proportion of installed capacity in practical production applications is increasing year on year, so that the stability of its operation becomes a central factor in determining the productivity of the wind farm in question. This paper takes a 5 MW wind turbine as the research object and proposes a parameter‐adaptive robust model predictive control method to achieve self‐optimization of controller parameters through a Bayesian optimization approach. A robust model predictive control strategy, aiming to reduce the power fluctuation while maximizing the power output, is developed in this paper to enhance the dynamic economic performance under uncertain wind speed variation. A Bayesian algorithm is used in this paper to optimize the parameters of the controller. Moreover, wind speeds are simulated using TurbSim for different turbulence intensities of 5%, 10%, and 15% turbulence. Finally, the robust model predictive control toolbox in MATLAB is designed and simulated. The results show that the operational instability of the wind energy system is overcome. Meanwhile, the robustness of the wind energy system operation is improved compared to the traditional model predictive control approach.

Analysis of the Sand Erosion Effect and Wear Mechanism of Wind Turbine Blade Coating

The wind–sand climate prevalent in the central and western regions of Inner Mongolia results in significant damage to wind turbine blade coatings due to sand erosion. This not only leads to a decline in power generation but also poses safety risks. This study replicated the wind–sand environment of Alashan and numerically simulated the erosion and wear process of the blade coatings of a 1.5 MW horizontal axis wind turbine under rotational conditions using the DPM model. Additionally, erosion tests were conducted on the operating wind rotor in a wind tunnel. The simulation results demonstrate that sand particle trajectories in the rotating domain are influenced by vortex, incoming wind speed, and sand particle size. For small-sized sand particles, variations in wind speed do not substantially alter the number of particles in contact with the wind turbine blades. However, alterations in the momentum of these particles lead to changes in the impact force on the coating surface. Conversely, the change of wind speed will not only alter the number of large-size sand particles in contact with the wind rotor but also modify the impact force on the coating surface. Furthermore, after impacting the blade, small sand particles continue to move along an approximate helical trajectory with the airflow, while large-size sand particles swiftly rebound. Through statistical analysis of erosion pits on the blade surface after the erosion experiments, it was observed that, in comparison among the leading edge, windward side, trailing edge, and leeward side, the leading edge presents the greatest number of erosion pits, whereas the leeward side has the fewest. Along the spanwise direction, the 0.7R-blade tip segment exhibits the highest count, while the blade root-0.3R section displays the fewest number of pits. The wear morphology of the blade coating was observed from the blade root to tip. The leading edge coating exhibits a range from shallow pits to coating flaking and deeper gouge pits. On the windward side, the coating displays wear patterns varying from tiny cutting pits to cutting marks, and then to gouge pits and coating flaking. Erosion morphology of the trailing edge evolves from only minor scratches to spalling pits, further deepening and enlarging. These research findings provide a basis for the study of zoning-adapted coating materials for wind turbine blades in wind–sand environments.

Robust model predictive control of wind turbines based on Bayesian parameter self-optimization

This paper studies the effect of different turbulent wind speeds on the operation of wind turbines. The proportion of wind power in the field of new energy generation has increased massively and has gained wide application and attention. However, the smooth operation and the stability of the output power of the wind power generation system are susceptible to wind speed fluctuations. To tackle this problem, this paper takes a 5 MW horizontal axis wind turbine as the research object that proposes a parameter adaptive robust control method to achieve self-optimization of controller parameters by means of Bayesian optimization. The 5 MW wind turbine model is utilized to verify the feasibility of the algorithm by combining the wind speed types commonly found in a high-altitude region in northwestern. The simulation results validate the effectiveness of the proposed scheme. The outcomes demonstrate that Bayesian optimization can significantly decrease the effects of wind speed instability. The output power increases by 1.9% on average at low wind speed and stabilizes on 5 MW at high wind speed. Therefore, the stable controller for wind power output is the robust model predictive controller with parameter improvement.

Numerical study of the unsteady blade root aerodynamics of a 2 MW wind turbine equipped with vortex generators

Abstract. In order to design vortex generators for modern multi-megawatt wind turbines accurately, the 3D behaviour of the boundary layer has to be considered. Due to the rotation of the blade, the lift-enhancing rotational augmentation has a considerable impact, especially in the inner blade sections. To investigate the interaction of vortex generators and rotational augmentation, high-fidelity computational flow simulations by means of unsteady Reynolds-averaged Navier–Stokes methods are presented for a rotating blade of a generic 2 MW horizontal-axis wind turbine. The inner blade section is analysed with and without vortex generators for two different pitch settings, including one causing largely separated flow. Two ways of placing the vortex generators on the blade with different radial starting positions are investigated in order to find out if the coexistence of the two lift-enhancement methods (i.e. rotational augmentation and vortex generators) is beneficial. All simulations are performed with the flow solver FLOWer, and the vortex generators are modelled by the introduction of source terms into the computational domain through a so-called BAY (Bender–Anderson–Yagle)-type model. For the case without vortex generators, it is found that the strength of rotational augmentation largely depends on the effective angles of attack (i.e. the pitch setting). For the case with lower effective angles of attack, rotational augmentation is a cyclic phenomenon, whereas for the case with higher effective angles of attack, it generates large loads in the inner root section due to a constant centrifugal pumping mechanism in time. The results from the cases with vortex generators display a rather destructive interaction of vortex generators and rotational augmentation on the torque. For low effective angles of attack and thus attached flow conditions, vortex generators exhibit slight losses compared to the case without vortex generators, as they inhibit spanwise flow through rotational augmentation. For high effective angles of attack, the vortex generators placed over 30 % of the blade produce an increase of 3.28 % in torque compared to the case without vortex generators and high centrifugal pumping.

Multi-Megawatt Horizontal Axis Wind Turbine Blade Optimization Based on PSO Method

Blade optimization methods are crucial for wind turbine design. In this research, a new set of values for the parameters of the Particle Swarm Optimization (PSO) method is proposed, and its effects on the enhancement of the power generation of the NREL WP-Baseline 1.5 MW horizontal axis wind turbine are investigated. First, the PSO parameters are tuned, and the convergence speed and the optimal accuracy of the objective function are improved. Then, the Class/Shape Transformation (CST) method is employed, and an appropriate order of the shape function polynomial is selected. In the third step, the WP-Baseline 1.5 MW blade is optimized according to the tuned PSO parameters, and the airfoil is represented by CST algorithms. Later, a CFD model, including 37 million cells and an IDDES turbulence model, was validated and used for a comparison of the power generation of the original and optimized blades. The optimized blade produced more power for all wind speeds above 4.5 m/s, with a maximum of 13.8% at 10 m/s and +7.25% at the rated wind speed (11.5 m/s). It should be noted that since the algorithms, tunings, and techniques adopted in the present study were general, the presented method can be used as a systematic approach for the aerodynamics shape optimization of multi-megawatt HAWTs.

Preliminary Analysis on the Hydrostatic Stability of a Self-Aligning Floating Offshore Wind Turbine

There exist vast areas of offshore wind resources with water depths greater than 100 m that require floating structures. This paper provides a detailed analysis on the hydrostatic stability characteristics of a novel floating wind turbine concept. The preliminary design supports an 8 MW horizontal-axis wind turbine with a custom self-aligning single-point mooring (SPM) floater, which is to be constructed within the existing shipyard facilities in the Maltese Islands, located in the Central Mediterranean Sea. The theoretical hydrostatic stability calculations used to find the parameters to create the model are validated using SESAM®. The hydrostatic stability analysis is carried out for different ballast capacities whilst also considering the maximum axial thrust induced by the rotor during operation. The results show that the entire floating structure exhibits hydrostatic stability characteristics for both the heeling and pitching axes that comply with the requirements set by the DNV ST-0119 standard. Numerical simulations using partial ballast are also presented.

Active vibration control of horizontal-axis wind turbine blades using disturbance observer-based boundary control approach

This paper addresses the issue of controlling vibration in horizontal-axis wind turbine (HAWT) blades under unknown boundary and distributed disturbances using an observer-based boundary control approach. In this regard, an actuator configuration, involving four active tendons mounted on the tip of the blade, is proposed to generate the out-of-plane and in-plane boundary control forces. The out-of-plane and in-plane governing equations are given as a set of PDEs and ODEs under parametric and direct excitations using Rayleigh beam theory including rotary inertia. A new disturbance observer is introduced to estimate boundary disturbances and subsequently combined with a new boundary control law for alleviating the HAWT blade vibration in the presence of unknown but bounded distributed disturbances. The uniform boundedness of the closed-loop system under unknown bounded distributed disturbances is confirmed via employing the Lyapunov’s direct method together with LaSalle–Yoshizawa’s theorem. Moreover, it is proved that the closed-loop system is uniformly exponentially stable in the absence of distributed and boundary disturbances. The reference NREL 5 MW HAWT blade is selected as the case study and the blade element momentum theory (BEMT) is employed to compute the aerodynamic load. Then, the open-loop and closed-loop responses of the blade under wind shear inflow and a predefined boundary disturbance are compared to demonstrate the performance of the closed-loop system in operational conditions.

A neural networking based fault detection system for pitch and yaw control of a HAWT under different operating conditions

A fault detection system for the pitch and yaw control of a 1.5 MW horizontal axis wind turbine based on a data-driven technique is proposed. The impact of high ambient temperature and dust accumulation on the proposed fault detection technique was investigated. The system was modeled using the simulation programs FAST, TurbSim, and MATLAB under various operating scenarios and wind speeds. Pitch angle faults from −10° to 15°, blade imbalance faults from −3% to 7%, and nacelle-yaw angle faults from −10° to 20° were investigated. Furthermore, fault detection was considered under different operating temperatures. The Fast Fourier Transform (FFT) was applied to the Tower Top Deflection (TTD) data. Results show that the peaks of the TTD while applying faults to the blade are in the range of 5.09 to 21.42 Hz. YAW faults produce a single peak at 5.67 Hz while blade faults have two peaks. Moreover, the ambient temperature affects both the frequency and amplitude spectrum values. The TTD data were utilized to develop a Neural Network that can identify the errors in the pitch and yaw control systems. This network categorizes the faults into three categories with a best validation performance of 0.0086482.

Stress Coupling Analysis and Failure Damage Evaluation of Wind Turbine Blades during Strong Winds

Blades in strong wind conditions are prone to various failures and damage that is due to the action of random variable amplitude loads. In this study, we analyze the failure of 1.5 MW horizontal axis wind turbine blades. The computational fluid dynamics unsteady calculation method is used to simulate the aerodynamic load distribution on the blade. Fluid–structure coupling methods are applied to calculate the blade stress. The results show that the equivalent stress of the blade is the largest when the azimuth angle is 30°, and the maximum equivalent stress is 20.60 MPa. There are obvious stress peaks in six sections, such as r/R = 0.10 (the span length of blade/the full length of the blade = 0.10). The frequency of damage that is caused by the stress in each area of the blade is determined based on the blade damage. The frequency of gel coat cracking in the blade tips and leaves is 77.78% and 22.22%, respectively, and the frequency of crack occurrence is 87.75%, 10.20% and 2.05%, respectively. By combining the stress concentration area and the damage results, the cause of blade damage is determined, which can replace the traditional inspection methods and improve the inspection efficiency.

A Fault Detection System for The Yaw Control of A HAWT Based on Neural Networking

The objective of the yaw control system in a horizontal axis wind turbine (HAWT) is to follow the wind direction with a minimum error. In this paper, a data driven fault detection approach of a HAWT is applied. Three simulation programs were utilized in order to model a 1.5 MW HAWT. These programs are Fatigue, Aerodynamics, Structures, and Turbulence(FAST), TurbSim, and MATLAB. The approach is implemented under normal operating scenarios while considering different wind velocities. Different kinds of faults were applied to the system for a nacelle-yaw angle error ranging from -10° to +20°. The simulation results of the Tower Top Deflection (TTD) in the time domain were transferred into frequency domain by Fast Fourier Transform (FFT). The output variables were used in order to build a Neural Networking, which will monitor the performance of the wind turbine. The built Neural Networking will also provide an early fault detection to avoid the operating conditions that lead to sudden turbine breakdown. The present work provides initial results that are useful for remote condition monitoring and assessment of a 1.5MW HAWT. The simulation results indicate that the implemented Neural Networking can achieve improvement of the wind turbine operation and maintenance level.

Structural response analysis of wind turbine under different wind speeds

Taking a 2 MW horizontal axis wind turbine in a wind farm in Northwest China as the research object, the structural response analysis of wind turbine considering fluid structure coupling effect under different inflow was carried out by using ANSYS Workbench software. The results show that when the incoming wind speed is cut-in wind speed, the displacement and stress change slightly; when the incoming wind speed is between the cut-in and cut-out wind speed, the structural response law of the wind turbine is the same. The maximum of displacement and stress increase with the increase of wind speed, and the maximum displacement of the blade is located in the tip, and the maximum stress of the blade is concentrated in the middle of the blade; The maximum displacement of the tower is located at the top, and the maximum stress of the tower is concentrated at the bottom. The results have important reference value for the design and safe operation of wind turbine.

Aeroelastic stability analysis and failure damage evaluation of wind turbine blades under variable conditions

ABSTRACT Failure during the start and brake processes of a 1.5 MW horizontal axis wind turbine blade was examined using a measured wind field with fluid-structure coupling. The maximum blade displacement and stress with angular acceleration during the start process were 7.14% and 16.27%, respectively, larger than those without acceleration, whereas during braking they were 37.71% and 26.96% larger, respectively, without acceleration. Further, angular acceleration had a greater impact on the second-order frequency of vibration than the first-order, significantly impacting the braking process. The maximum dynamic stress and amplitude of the blades during starting were 4.35 MPa and 0.56 m, and during braking were 35.86 MPa and 3.13 m, respectively. Based on drone images of the blades, several failure modes were identified. This research will provide key inspection area guidance for employing drones to inspect blades to improve inspection efficiency. A large amount of damage images are collected and classified into damage levels, and an image processing system are established, which can quickly identify damage characteristics of the blade and export the inspection report quickly and accurately. Through a large number of drone detection experiments, this technology has a wide range of application prospects and extremely high efficiency.

Numerical simulation of icing effect on aerodynamic characteristics of a wind turbine blade

Icing accretion on wind turbine will degrade its performance, resulting in reduction of output power and even leading to accidents. For solving this problem, it is necessary to predict the icing type and shape on wind turbine blade, and evaluate the variation of aerodynamic characteristics. In this paper the icing types and shapes in presence of airfoil, selected from blade of 1.5 MW horizontal-axis wind turbine, are simulated under different ambient temperatures and icing time lengths. Based on the icing simulation results, the aerodynamic characteristics of icing airfoils are simulated, including lift and drag coefficient, lift-drag ratio, etc. The simulation results show that the glaze ice with two horns presents on airfoil under high ambient temperature such as -5?C. When ambient temperatures are low, such as -10?C and -15?C, the rime ices with streamline profiles present on the airfoil. With increase in icing time the lift forces and coefficients decrease, and the drag ones increase. According to the variations of lift-drag ratios of icing airfoil, the aerodynamic performance of airfoil deteriorates in the presence of icing. The glaze ice has great effect on aerodynamic characteristics of airfoil. The research findings lay theoretical foundation for icing wind tunnel experiment.

Design and analysis of 5 MW horizontal axis wind turbine

The need of renewable energy sources is growing. Wind energy is the important sources of renewable energy. In the wind energy sector Horizontal axis wind turbines are the major devices used for the production of electricity. Blade is the most important part of HAWT. Lift force and drag force has an important role in the performance of a wind turbine. The main aim of this work is to make CFD analysis of optimum blade attack angle using k-e model. The moments are calculated for the blade angle varies 10 to 85 degree. The wind velocities considered for the study are 3 m/s, 12.5 m/s and 25 m/s. The result obtained from this simulation is the optimum blade attack angle where the maximum moment produced at the given wind velocities.

Identification of cumulative damage at the blade root of AB92 blade using Palmgren-Miner’s rule

This study presents the identification of cumulative damage at the blade root of AVANTIS AB92 wind turbine blade by evaluating the simulations generated output obtained from GH Bladed software. The blade length was 45.3 m and consisted of six (6) different airfoils. The blade material was made of GRP/Epoxy with a weight of 10.2 tons. At the blade root, the bolt hole circle diameter was 2.3 m with a 1.3 m distance from hub centre to rotor shaft flange. The fatigue loads at the blade connection of AB92 were performed according to Germanischer Lloyd guideline for a 2.5 MW horizontal axis wind turbine generator with wind class IEC IIA. The simulations were performed when the turbine operates during power production with and without occurrence of fault with wind condition satisfying the normal turbulence model. Design load cases such as during start-up and normal shutdown were also carried out with wind condition similar to normal wind profile model. The fatigue load cases at the blade connection were post-processed by determining the rainflow cycle counting and damage equivalent loads using GH Bladed software. Statistical estimation models such as graphical and exponential methods were also used to predict the Weibull parameters. The total fatigue damages due to bending moments and torsion at the blade connection were evaluated using the Palmgren-Miner’s rule at different expected behaviour of S-N curves. Calculation results indicate that the total fatigue damage due to torsion, flapwise and edgewise bending moments at the blade connection of AB92 when the slope parameter of S-N curve i.e., m = 3 are less than unity with values of 0.8702, 0.0354 and 0.0180, respectively.

An Induction Curve Model for Prediction of Power Output of Wind Turbines in Complex Conditions

Power generation from wind farms is traditionally modeled using power curves. These models are used for assessment of wind resources or for forecasting energy production from existing wind farms. However, prediction of power using power curves is not accurate since power curves are based on ideal uniform inflow wind, which do not apply to wind turbines installed in complex and heterogeneous terrains and in wind farms. Therefore, there is a need for new models that account for the effect of non-ideal operating conditions. In this work, we propose a model for effective axial induction factor of wind turbines that can be used for power prediction. The proposed model is tested and compared to traditional power curve for a 2.5 MW horizontal axis wind turbine. Data from supervisory control and data acquisition (SCADA) system along with wind speed measurements from a nacelle-mounted sonic anemometer and turbulence measurements from a nearby meteorological tower are used in the models. The results for a period of four months showed an improvement of 51% in power prediction accuracy, compared to the standard power curve.