Intelligent slope-based maximum power point searching algorithm for fixed-pitch horizontal-axis wind energy systems

This report presents the study of fluid-structure interaction (FSI) of a 5kW horizontal axis wind turbines (HAWT). The motivation of the current investigation is to address the FSI problem of HAWT in the whole flow field analysis with hybrid turbulence model method which is used to find out the flow and structure characteristics of wind turbine in operation under different tip speed ratio (TSR). The target of current work is to obtain detailed information of flow field and structure response simultaneously using the finite element analysis (FEA) method as well as providing new reliable and accurate approach which could be quickly and economically employed in wind turbine FSI problem analysis. In this report, a detailed and comprehensive literature review related to FSI problem of wind turbine has been presented and includes aerodynamic, wind turbine theory, computational fluid dynamic, fluid structure interaction and aeroelastic stability. A 5kW wind turbine is designed according to blade element momentum (BEM) method and a 3D wind turbine modeling is generated in SolidWorks. The 3D wind turbine modeling is imported into FEA software by coupling with the structure domain and the fluid domain to achieve FSI analysis and different TSR are applied to the computational fluid dynamics (CFD) analysis to gain the wind turbine operation information under different scenarios. The simulation results are investigated to reveal the influence of the FSI phenomenon on wind turbine performance. Analysis of wind turbine aeroelastic stability is conducted to prevent blade from experiencing flutter problem. A multiple objective optimization method for wind turbine design including aerodynamic and structure has been developed to improve wind turbine performance. The flow field analysis results showed that the strength of vortex at the tip and root of the blade increases as wind speed increases when wind turbine is under operating conditions. With wind speed of 10m⁄s, most of the flow over the lower surface remains attached and the wind turbine blade was running under design condition. As the wind speed increases, flow separation emerges. When the wind speed increasing to 16m⁄s, the wind turbine blade works under deep stall condition. The wind turbine power coefficient drops continuously from 0.46 to 0.22, as wind speed increased from 10m⁄s to 20m⁄s. The comparison of wind turbine power and torque coefficient under different CFD configuration shows the advantage of whole flow field analysis with hybrid turbulence model. The structural analysis results demonstrated that most of the pressure force acts at a region around the 1⁄4 chord from the leading edge of the blade under operating condition and the displacement of blade tip in flap direction is bigger than those in the other directions. Modal analysis results deduced that flap is the main type of vibration in first and second modes. The difference of natural frequency between single blade and blade rotor becomes larger as vibration order increases. The dynamic performances of wind turbine blade and rotor are totally different and show the whole flow field method is better than the one third domain method. The wind turbine aeroelastic analysis results illustrate that the bending frequency and torsion frequency are around 23.94Hz and 38.46Hz respectively under TSR=4 and both move towards 30Hz under TSR=1.7. When TSR is smaller than 1.7 the wind turbine will experience flutter due to the overlapping of bending and torsion frequencies. The multiple objectives optimization method takes the aerodynamic performance and blade loading into account to gain better design parameter. The comparison between initial and optimal design shows that optimized method could provide higher electrical energy around 1073kW•h per annum under rated wind speed. The optimized wind turbine critical flutter wind speed will increase from initial design speed of 35m/s to 38m/s under optimization design.

During recent years, wind energy has moved from an emerging technology to a nearly competitive technology. This fact, coupled with an increasing global focus on environmental concern and a political desire of a certain level of diversification in the energy supply, ensures wind energy an important role in the future electricity market. For this challenge to be met in a cost-efficient way, a substantial part of new wind turbine installations is foreseen to be erected in big onshore or offshore wind farms. This fact makes the production, loading and reliability of turbines operating under such conditions of particular interest.

In the wind turbine wake control research, the analytical wake model does not consider the influence of direct control parameters on the wind turbine wake flow field, and its prediction accuracy is by no means satisfying. The numerical simulation method can accurately predict the wake effect, but its low computational efficiency renders it unable to be used in the iterative control optimization study. In this paper, a new wake model coupled with the direct control parameters (tip speed ratio and pitch angle) of a single wind turbine is built based on the machine learning algorithm for which the widely applied Artificial Neural Network (ANN) is applied for instance. By combining the ANN wake model with different wake superposition models, the best combinatorial model for quantitative evaluation of multiple wake interferences is achieved, which not only has great accuracy but also ensures high calculation efficiency. On top of the established combinatorial wake model, three in-line wind turbines are investigated for assessing the effectiveness of wake control optimization with respect to the traditional greedy control. The results show that by optimizing the control parameters (tip speed ratio and pitch angle) of wind turbines, the total power of the three wind turbine units is increased by 1.15~3.48% depending on the incoming wind speeds and distances apart between wind turbines. The power variation of each wind turbine shows that the increase in total power is achieved by the decreased power of the first wind turbine and the increased power of the second and third wind turbines. The research verifies the effectiveness of adopting optimized wind turbine wake control on the total wind farm power improvement numerically.

Wind energy has emerged as one of the fastest-growing renewable energy sources, with horizontal axis wind turbines (HAWTs) predominantly deployed in large-scale applications.However, their effectiveness in urban environments is limited due to fluctuating wind patterns and space constraints.In contrast, vertical axis wind turbines (VAWTs) offer advantages such as compact design, low noise levels, and stable performance under low-speed and turbulent wind conditions, making them more suitable for urban settings.This review examines the performance characteristics of key VAWT configurations, including lift-based Darrieus turbines, drag-based Savonius turbines, and hybrid designs.Typical power coefficients (Cp) for these designs are approximately 0.4 for Darrieus, 0.15-0.2for Savonius, and 0.3-0.35 for hybrid models.Optimal operation is generally achieved at a tip speed ratio (TSR) of 0.45, corresponding to a maximum Cp of around 0.306 and a torque coefficient of 0.68.The review also identifies critical design and operational parameters influencing turbine performance.Finally, it highlights the need for continued research to enhance efficiency, reliability, and integration of VAWTs into future urban energy systems.

A vertical-axis wind turbine (VAWT) is a type of wind turbine where the main rotor shaft is set transverse to the wind (but not necessarily vertically) while the main components are located at the base of the turbine. The performance of a Vertical Axis Wind Turbine (VAWT) is closely related to its Tip Speed Ratio (TSR). It is not easy to know beforehand which TSR will result in maximum power extracted from the VAWT. The objective is to model and simulate a 2D H-type VAWT in an open-source OpenFOAM CFD solver. The turbulence model used is k-Omega SST (Shear Stress Transport), and the rotating domain is set up using Arbitrary Mesh Interface (AMI) and dynamicMeshDict in OpenFOAM. Due to the transient nature of the simulation, pimpleFoam solver is used to simulate VAWT. Forces and Moments are reported after certain timesteps to obtain the torque Vs. Time curve for different TSRs. The simulation is carried out for different TSRs, and the graph of Coefficient of Power (Cp) Vs. TSR is plotted. It is found that the Cp first increases with an increase in TSR up to 0.35, and then Cp decreases. Such type of analyses can be used as a low-cost basis to obtain boundary and initial conditions or obtain baseline input parameters for 3D simulation of VAWTs.

The aerodynamic performance of offshore floating wind turbines (OFWTs) is more complicated than onshore wind turbines due to 6‐degree of freedom (DOF) motion of the floating platform. In the current study, the aerodynamic analysis of a horizontal‐axis floating offshore wind turbine is performed with the aim of studying the effects of floating platform movement on the aerodynamic characteristics of the turbine in the presence of a pitch angle control system. The National Renewable Energy Laboratory (NREL) 5‐MW offshore wind turbine is selected as the baseline wind turbine. For this sake, the unsteady blade element momentum method with dynamic stall and dynamic inflow models have been employed to obtain the unsteady aerodynamic loads. The baseline pitch angle control system is assumed to be coupled with the aerodynamic model to maintain the rated condition of the wind turbine and also to approach a closer model of wind turbine. In case of pitching motion input, the reduction of mean power coefficient for tip speed ratios (TSRs) less that 7 is expected by an amount of 16% to 20% at pitch amplitude of 2° and frequency of 0.1 Hz. For high TSRs, the trend is reverse with respect to fixed‐platform case. The mean thrust coefficient is reduced for almost all range of TSRs with maximum loss of 37%. Moreover, the mean control pitch angle that is an index of control system effort is increased. The results also represent the importance of considering the pitch control system for aerodynamic analysis of disturbed OFWT.

PurposeThe rapid rising of renewable energy sources particularly wind energy cannot be ignored. The numerical increase in wind energy farms throughout the world is the best example. The purpose of this paper is to assess the basic question of whether wind characteristics affect the performance and cost of energy. The importance of this question cannot be ruled out while comparing renewable energy to a conventional form of energy more specifically especially for the developing country where the cost of energy is very high.Design/methodology/approachThe research design of this paper is consists of an assessment of local wind characteristics of the wind farm site using Weibull k and c parameters. The performance model is used to assess the performance of the wind turbine (WT) corresponding to local wind characteristics. The wind correlation with WT in terms of changing wind speed has been assessed to quantify the effects of wind speed on the WT behavior and failure of WT components. Similarly, the power curve of WT is assessed and compared with the International Electrotechnical Commission standards 61400-12-2. The WT power coefficient and tip speed ratio corresponding to wind speed is also investigated. The energy volume and cost of energy lost model is used to determine the cost and volume loss of energy/kWh of the wind farm.FindingsThe findings of practical wind farms showed that the wind conditions of the site are showing a strong tendency that can be determined from the results of Weibull k and c parameters. The k and c parameters are observed to be 3.44 and 9.16 m/s, respectively, for a period of a year. The standard deviation is observed to be 2.56 for a period of a year. WT shows the efficient behavior can be obtained from the power coefficient and tip speed of WT at different wind speeds. Also, wind farm observation showed that to be some increasing wind speed cause of based WT component failures. The results of energy volume and cost/kWh assessment showed that the major portion of energy volume and cost of energy is lost owing to network, voltage dip and frequency surge, electrical and mechanical components failures.Originality/valueGenerally, it can be concluded that the WTs are now able to cope with variable wind speeds. However, the results of this paper are showing that WT performance and availability decreased due to increased wind speeds. It can also be a reason to decreased volume and increase the cost of energy/kWh.

A biomimetic wind turbine inspired by Dryobalanops aromatica seed: Numerical prediction of rigid rotor blade performance with OpenFOAM®

As wind turbines operate within the atmospheric boundary layer (ABL), the study of their interaction with the ABL flow can help us better understand and predict their performance. In addition to the performance of wind turbines, this interaction has an effect on the flow both upwind and downwind (i.e., wake region) of the turbines. In particular, the study of turbine wakes is of great importance because they are the main cause of power losses and fatigue loads in wind farms. In the current thesis, four studies are conducted to fully examine the turbine interaction with the ABL flow, with an emphasis on turbine wakes. In the first study, a new analytical wake model is proposed and validated to predict the wind velocity distribution in the far-wake region, where downwind turbines usually operate. The proposed model is derived by applying the conservation of mass and momentum and assuming a Gaussian distribution for the velocity deficit in the wake. This simple model only requires one parameter to predict the velocity distribution in the far wake of a wind turbine. In general, it is found that the velocity deficit in the wake predicted by the proposed analytical model is in good agreement with the experimental and numerical data. Furthermore, the results show that the new model predicts the power extracted by downwind wind turbines more accurately than other common analytical models, some of which are based on less accurate assumptions like considering a top-hat shape for the velocity deficit. In the second study, wind tunnel measurements are carried out to systematically investigate turbine wakes under yawed conditions. The detailed experimental data are used to perform a budget study of the continuity and Reynolds-averaged Navier-Stokes equations. This theoretical analysis reveals some notable features of the wakes of yawed turbines, such as the asymmetric distribution of the wake skew angle with respect to the wake center. Under highly yawed conditions, the formation of a counter-rotating vortex pair in the wake cross-section as well as the vertical displacement of the wake center are also shown and analyzed. Finally, this study enables us to develop general governing equations upon which a simple and computationally inexpensive analytical model is built. The proposed model aims at predicting the wake deflection and the far-wake velocity distribution for yawed turbines. The findings of this study can be especially useful to assess the possibility of optimizing wind-farm power production by controlling the yaw angle of the turbines. In the third study, comprehensive wind tunnel experiments are performed to study the interaction of a turbulent boundary layer with a wind turbine operating under different tip-speed ratios and yaw angles. Force and power measurements are performed to characterize the wind turbine performance. Moreover, a high-resolution stereoscopic particle-image velocimetry (S-PIV) system and hot-wire anemometry are used to study the flow in the upwind, near-wake and far-wake regions. This study provides new insights on the turbine and flow characteristics such as the evolution of tip vortices and wake meandering. Finally, the last study concerns the design and the performance analysis of a new three-bladed horizontal-axis miniature wind turbine with a rotor diameter of $15$ cm. Due to its small size, this turbine is particularly suitable for studies of wind farm flows and the interaction of the turbine with an incoming boundary-layer flow. Special emphasis is placed on accurate measurements of the mechanical power extracted by the miniature turbine from the incoming wind. In order to do so, a new setup is developed to measure the torque of the rotor shaft. The thrust and power coefficients of the miniature turbine are found to be around $0.8$ and $0.4$ in optimal conditions, respectively, which are close to the ones of large-scale turbines in the field.

Experimental and numerical investigation of the effect of blade number on the aerodynamic performance of a small-scale horizontal axis wind turbine

Research of asymmetric airfoil on aerodynamic characteristics of vertical axis wind turbines

A novel control method for a fixed‐pitch variable speed wind turbine is introduced and experimental results are presented. The measured absorbed power and rotational speed, together with a look‐up table for the aerodynamic efficiency, are used to estimate the wind speed reaching the turbine as well as the tip speed ratio. Thereby, the control is independent on wind speed measurements and the wind turbine itself is used as an anemometer. Tip speed ratio control is implemented by comparing the estimated tip speed ratio to a reference value and adjusting the DC voltage level accordingly. Tip speed ratio control benefits from that the aerodynamic efficiency hardly varies with changing tip speed ratio when close to its optimum value. Experimental results from a 200 kW vertical axis wind turbine are presented. The voltage from the permanent magnet generator is passively rectified and the alternating DC voltage is then inverted, filtered, transformed, and grid connected. The estimated wind speed is compared with the measured wind speed. The absorbed power when tip speed ratio control has been implemented is shown. It is concluded that the presented control method works and some future improvements are discussed.

Magnus rotor is essentially a rotating cylinder that generates lift due to Magnus effect. The effect has been generating curiosity in a wide variety of fields ranging from sports to alternate energy. The wind turbine under investigation replaces tradition blades that have an airfoil cross-section, with such Magnus rotors. In this paper, Magnus wind turbines with three and five rotors have been analyzed at various velocity ratios and tip speed ratios. The primary motive is to find the best operating conditions for obtaining a higher lift to drag coefficient for both three and five rotor turbines, so that it can generate more power with the least available wind. It has been observed that the higher ratio of coefficient of lift to coefficient of drag values were obtained for lower values of tip speed ratio, which is in contrast to the requirement of higher tip speed ratios for turbines with airfoil cross-section. This translates to the fact that Magnus wind turbines can be an efficient solution to the generation of wind power with less noise generation, since the noise generated by a wind turbine decreases with decrease in the tip speed ratio.

This study investigates how ordinary atmospheric conditions induce systematic deviations from the nominal manufacturer's power curve of a modern wind turbine using a residual-based comparative power curve analysis. The approach directly compares theoretical power values with turbine-level SCADA measurements. It evaluates the difference between predicted and measured power as a continuous indicator of relative underperformance rather than as a classified anomaly. The dataset comprises wind speed, wind direction, air density, ambient temperature, cloud cover, solar irradiance, and measured electrical power from a Nordex N117/3600 wind turbine over a full annual period, complemented by temporally synchronized atmospheric data. Power residuals are analyzed as functions of wind speed and paired meteorological variables to reveal recurring deviation patterns and their physical context. The cumulative integration of positive residuals indicates an annual energy production loss of approximately 244,481 kWh, demonstrating that small but persistent power-curve departures accumulate into a substantial long-term deficit. The results show that performance deviations concentrate primarily in the partially loaded operating region and are strongly associated with variations in air density and wind regime. At the same time, temperature and radiative variables play a secondary role. The main contribution of this study is the presentation of a physically interpretable, residual-based performance deviation analysis that links power curve departures directly to atmospheric conditions and quantifies their cumulative energy impact without relying on predictive models or formal anomaly detection algorithms

This study utilises large-eddy simulation with the actuator line model to examine the effects of the tip speed ratio (TSR) on the wake-meandering characteristics of a wind turbine in uniform and turbulent inflows. It is shown that as the TSR grows, the onset position of the wake meandering moves closer to the rotor, and the magnitude of wake oscillation is stronger. This aligns with previous work showing that a higher TSR can accelerate the instability and breakdown of tip vortices. Without a nacelle, the Strouhal number of the wake meandering is found to be independent of the TSR under both the uniform and turbulent inflows. However, with a relatively large nacelle, the Strouhal number first increases and then decreases with TSR. Therefore, the current discovery elucidates the crucial role of the nacelle and clarifies the origin of the TSR dependence of the Strouhal number in wake meandering. In addition, the characteristic frequency of the wake meandering under the turbulent inflow is much smaller than that under the uniform inflow, because of the significant influence of the freestream turbulence. Furthermore, the proper orthogonal decomposition (POD) and spectral POD (SPOD) methods are employed to study the spatiotemporal characteristics of the meandering wake and its TSR dependence. It is found that the tip and root vortices are the prominent wake structures under the uniform inflow, whereas more complex multiscale structures from the interaction between the freestream turbulence and tip/root vortices exist under the turbulent inflow. Moreover, an amplitude modulation phenomenon of the POD time coefficients at the optimal TSR is observed in the uniform inflow case. Finally, a reduced-order model is constructed for predicting the wake dynamics by combining the SPOD and the ‘sparse identification of nonlinear dynamics’ algorithm with high accuracy and interpretability.