Optimized Design of Bio-Inspired Wind Turbine Blades

To enhance the aerodynamic performance of wind turbine blades,this study proposes the adoption of a bionic airfoil inspired by the aerodynamic shape of an eagle.Based on the blade element theory,a non-uniform extraction method of blade elements is employed for the optimization design of the considered wind turbine blades.Moreover,Computational Fluid Dynamics(CFD)is used to determine the aerodynamic performances of the eagle airfoil and a NACA2412 airfoil,thereby demonstrating the superior aerodynamic performance of the former.Finally,a mathematical model for optimizing the design of wind turbine blades is introduced and a comparative analysis is conducted with respect to the aerodynamic performances of blades designed using a uniform extraction approach.It is found that the blades designed using non-uniform extraction exhibit better aerodynamic performance.

Research on the Icing Diagnosis ofWind Turbine Blades Based on FS–XGBoost–EWMA

In winter,wind turbines are susceptible to blade icing,which results in a series of energy losses and safe operation problems.Therefore,blade icing detection has become a top priority.Conventional methods primarily rely on sensor monitoring,which is expensive and has limited applications.Data-driven blade icing detection methods have become feasible with the development of artificial intelligence.However,the data-driven method is plagued by limited training samples and icing samples;therefore,this paper proposes an icing warning strategy based on the combination of feature selection(FS),eXtreme Gradient Boosting(XGBoost)algorithm,and exponentially weighted moving average(EWMA)analysis.In the training phase,FS is performed using correlation analysis to eliminate redundant features,and the XGBoost algorithm is applied to learn the hidden effective information in supervisory control and data acquisition analysis(SCADA)data to build a normal behavior model.In the online monitoring phase,an EWMA analysis is introduced to monitor the abnormal changes in features.A blade icing warning is issued when themonitored features continuously exceed the control limit,and the ambient temperature is below 0℃.This study uses data fromthree icing-affected wind turbines and one normally operating wind turbine for validation.The experimental results reveal that the strategy can promptly predict the icing trend among wind turbines and stably monitor the normally operating wind turbines.

Nonlinear Flap-Wise Vibration Characteristics ofWind Turbine Blades Based onMulti-Scale AnalysisMethod

This work presents a novel approach to achieve nonlinear vibration response based on the Hamilton principle.We chose the 5-MW reference wind turbine which was established by the National Renewable Energy Laboratory(NREL),to research the effects of the nonlinear flap-wise vibration characteristics.The turbine wheel is simplified by treating the blade of a wind turbine as an Euler-Bernoulli beam,and the nonlinear flap-wise vibration characteristics of the wind turbine blades are discussed based on the simplification first.Then,the blade’s large-deflection flap-wise vibration governing equation is established by considering the nonlinear term involving the centrifugal force.Lastly,it is truncated by the Galerkin method and analyzed semi-analytically using the multi-scale analysis method,and numerical simulations are carried out to compare the simulation results of finite elements with the numerical simulation results using Campbell diagram analysis of blade vibration.The results indicated that the rotational speed of the impeller has a significant impact on blade vibration.When the wheel speed of 12.1 rpm and excitation amplitude of 1.23 the maximum displacement amplitude of the blade has increased from 0.72 to 3.16.From the amplitude-frequency curve,it can be seen that the multi-peak characteristic of blade amplitude frequency is under centrifugal nonlinearity.Closed phase trajectories in blade nonlinear vibration,exhibiting periodic motion characteristics,are found through phase diagrams and Poincare section diagrams.

Theoretical and Empirical Limits: Reexamining Betz’s Upper Limit towards a Practical Power Coefficients in Wind Turbines*

The aspiration of all wind turbine designers is to attain Betz’s upper limit, which represents the highest efficiency in wind energy extraction. Majority of working turbines operate slightly below this limit with an exception of a few operating in wind tunnels. This study proposes for a comprehensive reevaluation of Betz’s derivation, aiming to establish the gap between a theoretical power limit and a practical limit for realization. There are two common expressions for power coefficient giving the same optimal value of 59%, but they generate different power-coefficient curves when plotted against velocity ratios. This paper presents a new method being referred as “Direct Multiplication Fractional Change” (DMFC) for deriving power-coefficient curves in wind energy, and compares its generated curve with established models. Discrepancies in power-coefficient expressions are identified and harmonized. Three approaches, namely EVAM, LVM, and DMFCM, were used for the numerical derivation of cp in the study, with their evaluation summarized in a table. The study collaborates its findings with a formulated velocity-distance curve, commonly presented as a hypothetical velocity profile in some publications. The results from DMFCM indicate two distinct maxima for the power coefficient. On the front side of the disc, a maximum of 0.5 is achievable in practice, although it is not the highest theoretically. On the rear side, a theoretical maximum of 0.59 is observed, but this value is not attainable in practice. These maxima are separated by their positions along the line of flow relative to the disc. However, this approximation is limited to a streamlined flow model of the rotor disc.

Influence of Surface Ice Roughness on the Aerodynamic Performance of Wind Turbines

The focus of this research was on the equivalent particle roughness height correction required to account for the presence of ice when determining the performances of wind turbines.In particular,two icing processes(frost ice and clear ice)were examined by combining the FENSAP-ICE and FLUENT analysis tools.The ice type on the blade surfaces was predicted by using a multi-time step method.Accordingly,the influence of variations in icing shape and ice surface roughness on the aerodynamic performance of blades during frost ice formation or clear ice formation was investigated.The results indicate that differences in blade surface roughness and heat flux lead to disparities in both ice formation rate and shape between frost ice and clear ice.Clear ice has a greater impact on aerodynamics compared to frost ice,while frost ice is significantly influenced by the roughness of its icy surface.

A method for cleaning wind power anomaly data by combining image processing with community detection algorithms

Current methodologies for cleaning wind power anomaly data exhibit limited capabilities in identifying abnormal data within extensive datasets and struggle to accommodate the considerable variability and intricacy of wind farm data.Consequently,a method for cleaning wind power anomaly data by combining image processing with community detection algorithms(CWPAD-IPCDA)is proposed.To precisely identify and initially clean anomalous data,wind power curve(WPC)images are converted into graph structures,which employ the Louvain community recognition algorithm and graph-theoretic methods for community detection and segmentation.Furthermore,the mathematical morphology operation(MMO)determines the main part of the initially cleaned wind power curve images and maps them back to the normal wind power points to complete the final cleaning.The CWPAD-IPCDA method was applied to clean datasets from 25 wind turbines(WTs)in two wind farms in northwest China to validate its feasibility.A comparison was conducted using density-based spatial clustering of applications with noise(DBSCAN)algorithm,an improved isolation forest algorithm,and an image-based(IB)algorithm.The experimental results demonstrate that the CWPAD-IPCDA method surpasses the other three algorithms,achieving an approximately 7.23%higher average data cleaning rate.The mean value of the sum of the squared errors(SSE)of the dataset after cleaning is approximately 6.887 lower than that of the other algorithms.Moreover,the mean of overall accuracy,as measured by the F1-score,exceeds that of the other methods by approximately 10.49%;this indicates that the CWPAD-IPCDA method is more conducive to improving the accuracy and reliability of wind power curve modeling and wind farm power forecasting.

Data-Driven Modeling for Wind Turbine Blade Loads Based on Deep Neural Network

Blades are essential components of wind turbines.Reducing their fatigue loads during operation helps to extend their lifespan,but it is difficult to quickly and accurately calculate the fatigue loads of blades.To solve this problem,this paper innovatively designs a data-driven blade load modeling method based on a deep learning framework through mechanism analysis,feature selection,and model construction.In the mechanism analysis part,the generation mechanism of blade loads and the load theoretical calculationmethod based on material damage theory are analyzed,and four measurable operating state parameters related to blade loads are screened;in the feature extraction part,15 characteristic indicators of each screened parameter are extracted in the time and frequency domain,and feature selection is completed through correlation analysis with blade loads to determine the input parameters of data-driven modeling;in the model construction part,a deep neural network based on feedforward and feedback propagation is designed to construct the nonlinear coupling relationship between the unit operating parameter characteristics and blade loads.The results show that the proposed method mines the wind turbine operating state characteristics highly correlated with the blade load,such as the standard deviation of wind speed.The model built using these characteristics has reasonable calculation and fitting capabilities for the blade load and shows a better fitting level for untrained out-of-sample data than the traditional scheme.Based on the mean absolute percentage error calculation,the modeling accuracy of the two blade loads can reach more than 90%and 80%,respectively,providing a good foundation for the subsequent optimization control to suppress the blade load.

Effect of Rigid Pitch Motion on Flexible Vibration Characteristics of a Wind Turbine Blade

Adynamic pitch strategy is usually adopted to improve the aerodynamic performance of the blade of awind turbine.The dynamic pitch motion will affect the linear vibration characteristics of the blade.However,these influences have not been studied in previous research.In this paper,the influences of the rigid pitch motion on the linear vibration characteristics of a wind turbine blade are studied.The blade is described as a rotating cantilever beam with an inherent coupled rigid-flexible vibration,where the rigid pitch motion introduces a parametrically excited vibration to the beam.Partial differential equations governing the nonlinear coupled pitch-bend vibration are proposed using the generalized Hamiltonian principle.Natural vibration characteristics of the inherent coupled rigid-flexible system are analyzed based on the combination of the assumed modes method and the multi-scales method.Effects of static pitch angle,rotating speed,and characteristics of harmonic pitch motion on flexible natural frequencies andmode shapes are discussed.It shows that the pitch amplitude has a dramatic influence on the natural frequencies of the blade,while the effects of pitch frequency and pith phase on natural frequencies are little.

Research on Fatigue Damage Behavior of Main Beam Sub-Structure of Composite Wind Turbine Blade

Given the difficulty in accurately evaluating the fatigue performance of large composite wind turbine blades(referred to as blades),this paper takes the main beam structure of the blade with a rectangular cross-sectionas the simulation object and establishes a composite laminate rectangular beam structure that simultaneouslyincludes the flange,web,and adhesive layer,referred to as the blade main beam sub-structure specimen,throughthe definition of blade sub-structures.This paper examines the progressive damage evolution law of the compositelaminate rectangular beam utilizing an improved 3D Hashin failure criterion,cohesive zone model,B-K failurecriterion,and computer simulation technology.Under static loading,the layup angle of the anti-shear web hasa close relationship with the static load-carrying capacity of the composite laminate rectangular beam;under fatigueloading,the fatigue damage will first occur in the lower flange adhesive area of the whole composite laminaterectangular beam and ultimately result in the fracture failure of the entire structure.These results provide a theoreticalreference and foundation for evaluating and predicting the fatigue performance of the blade main beamstructure and even the full-size blade.

Flashover Probability of Wind Turbine Blade and Impact of Strong Electromagnetic Pulse from Lightning Strikes on Wind Turbine Safety

This paper systematically studies the flashover probability of wind turbine blade lightning arrester and the impact of strong electromagnetic pulses on the local and surrounding wind turbines during lightning strikes.The research results indicate that the flashover probability of direct lightning strikes by the wind turbine blade lightning arrester is almost negligible,and the strong electromagnetic pulse of wind turbine blade during lightning strikes has a serious impact on the electronic equipment of the machine,while the impact on the surrounding wind turbine is relatively small.At the same time,the calculation formula for the reflection of lightning current on the carbon brush between the wind turbine hub and the engine compartment during the flashing of the wind turbine blades is provided,and the calculation method for calculating the spatial gradient distribution of electromagnetic field intensity using Biot-Savart Law theorem is applied.The limitations of using wind turbine blades for lightning protection are pointed out,and a technical route for achieving wind turbine lightning safety is proposed,which can be used as a reference for wind turbine lightning protection technicians.

Wind Turbine Noise Reduction through Blade Retrofitting

This paper outlines a plan for the effective reduction of the audible sound level produced by aerodynamic noise from the power-generating turbine blades. The contribution of aerodynamic noise can be divided into two categories: inflow turbulence and airfoil self-noise. The base model and retrofit blade designs were modeled in SolidWorks. Subsequently, noise prediction simulations were conducted and compared to the base blade model to determine which modification provided the greatest benefit using SolidWorks Flow Simulation. The result of this project is a series of blade retrofit recommendations that produce a more acoustically efficient design and reduce noise complaints while enabling turbines to be placed in locations that require quieter operations.

Numerical investigation on the flow and power of small-sized multi-bladed straight Darrieus wind turbine

Straight Darrieus wind turbine has attractive characteristics such as the ability to accept wind from random direction and easy installation and maintenance. But its aerodynamic performance is very complicated,especially for the existence of dynamic stall. How to get better aerodynamic performance arouses lots of interests in the design procedure of a straight Darrieus wind turbine. In this paper,mainly the effects of number of blades and tip speed ratio are discussed. Based on the numerical investigation,an assumed asymmetric straight Darrieus wind turbine is proposed to improve the averaged power coefficient. As to the numerical method,the flow around the turbine is simulated by solving the 2D unsteady Navier-Stokes equation combined with continuous equation. The time marching method on a body-fitted coordinate system based on MAC (Marker-and-Cell) method is used. O-type grid is generated for the whole calculation domain. The characteristics of tangential and normal force are discussed related with dynamic stall of the blade. Averaged power coefficient per period of rotating is calculated to evaluate the eligibility of the turbine.

Videometric research on deformation measurement of large-scale wind turbine blades

Utilization of wind energy is a promising way to generate power,and wind turbine blades play a key role in collecting the wind energy effectively.This paper attempts to measure the deformation parameter of wind turbine blades in mechanics experiments using a videometric method. In view that the blades experience small buckling deformation and large integral deformation simultaneously, we proposed a parallel network measurement(PNM) method including the key techniques such as camera network construction,camera calibration,distortion correction,the semi-automatic high-precision extraction of targets,coordinate systems unification,and bundle adjustment,etc. The relatively convenient construction method of the measuring system can provide an abundant measuring content,a wide measuring range and post processing.The experimental results show that the accuracy of the integral deformation measurement is higher than 0.5 mm and that of the buckling deformation measurement higher than 0.1mm.

Maximum Power Point Tracking in Variable Speed Wind Turbine Based on Permanent Magnet Synchronous Generator Using Maximum Torque Sliding Mode Control Strategy

The present study was carried out in order to track the maximum power point in a variable speed turbine by minimizing electromechanical torque changes using a sliding mode control strategy. In this strategy, first, the rotor speed is set at an optimal point for different wind speeds. As a result of which, the tip speed ratio reaches an optimal point, mechanical power coefficient is maximized, and wind turbine produces its maximum power and mechanical torque. Then, the maximum mechanical torque is tracked using electromechanical torque. In this technique, tracking error integral of maximum mechanical torque, the error, and the derivative of error are used as state variables. During changes in wind speed, sliding mode control is designed to absorb the maximum energy from the wind and minimize the response time of maximum power point tracking(MPPT). In this method, the actual control input signal is formed from a second order integral operation of the original sliding mode control input signal. The result of the second order integral in this model includes control signal integrity, full chattering attenuation, and prevention from large fluctuations in the power generator output. The simulation results, calculated by using MATLAB/m-file software, have shown the effectiveness of the proposed control strategy for wind energy systems based on the permanent magnet synchronous generator(PMSG).

Dynamic Characteristics Analysis of the Offshore Wind Turbine Blades

The topic of offshore wind energy is attracting more and more attention as the energy crisis heightens.The blades are the key components of offshore wind turbines,and their dynamic characteristics directly determine the effectiveness of offshore wind turbines.With different rotating speeds and blade length,the rotating blades generate various centrifugal stiffening effects.To directly analyze the centrifugal stiffening effect of blades,the Rayleigh energy method (REM) was used to derive the natural frequency equation of the blade,including the centrifugal stiffening effect and the axial force calculation formula.The axial force planes and the first to third order natural frequency planes which vary with the rotating speed and length were calculated in three-dimensional coordinates.The centrifugal stiffening coefficient was introduced to quantitatively study the relationship between the centrifugal stiffening degree and the rotating speed,and then the fundamental frequency correction formula was built based on the rotating speed and the blade length.The analysis results show that the calculation results of the fundamental frequency correction formula agree with the theoretical calculation results.The error of calculation results between them is less than 0.5%.

Dynamic modeling and direct power control of wind turbine driven DFIG under unbalanced network voltage conditions

This paper proposes an analysis and a direct power control (DPC) design of a wind turbine driven doubly-fed induction generator (DFIG) under unbalanced network voltage conditions. A DFIG model described in the positive and negative synchronous reference frames is presented. Variations of the stator output active and reactive powers are fully deduced in the presence of negative sequence supply voltage and rotor flux. An enhanced DPC scheme is proposed to eliminate stator active power oscillation during network unbalance. The proposed control scheme removes rotor current regulators and the decomposition processing of positive and negative sequence rotor currents. Simulation results using PSCAD/EMTDC are presented on a 2-MW DFIG wind power generation system to validate the feasibility of the proposed control scheme under balanced and unbalanced network conditions.

A Sliding Mode Approach to Enhance the Power Quality of Wind Turbines Under Unbalanced Voltage Conditions

An integral terminal sliding mode-based control design is proposed in this paper to enhance the power quality of wind turbines under unbalanced voltage conditions. The design combines the robustness, fast response, and high quality transient characteristics of the integral terminal sliding mode control with the estimation properties of disturbance observers. The controller gains were auto-tuned using a fuzzy logic approach.The effectiveness of the proposed design was assessed under deep voltage sag conditions and parameter variations. Its dynamic response was also compared to that of a standard SMC approach.The performance analysis and simulation results confirmed the ability of the proposed approach to maintain the active power,currents, DC-link voltage and electromagnetic torque within their acceptable ranges even under the most severe unbalanced voltage conditions. It was also shown to be robust to uncertainties and parameter variations, while effectively mitigating chattering in comparison with the standard SMC.

Diagnosis Technology for the Icing Status of Wind Turbine Blades Based on Vibration Detection

对不同覆冰状态下的风力机叶片动力特性进行了模拟实验研究，定义叶片覆冰状态参数，包括覆冰区域起点参数、覆冰区域长度参数和覆冰厚度参数。利用人工环境实验室和模态分析系统建立风力机叶片覆冰振动测试实验台，对风力机模拟叶片在不同覆冰状态下进行模态分析，从叶片的曲率模态参数中提取判断风力机叶片覆冰参数的特征值指标，从实验结果获得的特征值较准确地诊断出风力机模拟叶片覆冰状态。通过仿真计算得到叶片结构的质量变化率和抗弯刚度变化率重合点。上述仿真及实验结果表明风力机叶片覆冰诊断理论方法以及技术具备正确性与可行性。

Experimental study of the effect of slotted blades on the Savonius wind turbine performance

This study investigates the effect of Reynolds number on the performance of Savonius wind turbine with slotted blades.The turbine performance investigation was based on the torque coefficient(Ct),power coefficient(Cp),and tip speed ratio(TSR).The experiment used two number of blade configuration,blade overlap ratio of 10%,12.5%and 20%,slotted position of 15%,20%,25%and 35%,and also slotted gap width of 3 mm,5 mm,7 mm,and 9 mm.The wind speed carried out in this experiment are 5.94 m/s,6.46 m/s,6.99 m/s,and 7.27 m/s,which are generated from the fan blowers as a wind source.The Savonius turbine with 10%overlap ratio shows the best performance.The highest Cp obtained is 0.138 by the variation of a 3 mm gap with Re of 1.44×10^(4) and 0.526 TSR.

Comparative Study on Tree Classifiers for Application to Condition Monitoring ofWind Turbine Blade through Histogram Features Using Vibration Signals: A Data-Mining Approach

Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources.The wind turbine is an essential system used to change kinetic energy into electrical energy.Wind turbine blades,in particular,require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost.The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features.In this study,blade bend,hub-blade loose connection,blade erosion,pitch angle twist,and blade cracks were simulated on the blade.This problem is formulated as a machine learning problem which consists of three phases,namely feature extraction,feature selection and feature classification.Histogram features are extracted from vibration signals and feature selection was carried out using the J48 decision tree algorithm.Feature classification was performed using 15 tree classifiers.The results of the machine learning classifiers were compared with respect to their accuracy percentage and a better model is suggested for real-time monitoring of a wind turbine blade.