Wind Turbine Simulator Research Articles

Deep learning predictions of unsteady aerodynamic loads on an airfoil model pitched over the entire operating range

For the design and certification of wind turbines, it is essential to provide fast and accurate unsteady aerodynamic load prediction models for the whole operational range of angle of attack, up to 180° for vertical-axis and 90° for horizontal-axis wind turbines. This work describes a computationally efficient unsteady forces prediction model based on a deep learning approach, namely the bidirectional long short-term memory (BiLSTM) algorithm, for an airfoil pitched over the full operational range of angles of attack up to 180°. No model has been developed to capture the unsteady forces at high angles of attack. Novel features based on operating conditions and the steady polars of the airfoil are used as inputs for the BiLSTM model. Direct measurements of steady and unsteady forces on a NACA 0021 airfoil model were conducted at reduced frequencies up to 0.075 and a Reynolds number of 120 000 in an open-jet wind tunnel for model learning and testing. The unsteady forces vary significantly from the steady values at high pitching amplitudes and post-stall angles, which, if not accounted for when simulating wind turbine performance, would result in inaccurate predictions. Furthermore, measurements revealed the effect of unsteady vorticity development and shedding on aerodynamic forces under forward and reverse flow conditions. The BiLSTM model is capable of capturing the underlying physics of unsteady aerodynamic forces under extreme operating conditions.

A RANS-based surrogate model for simulating wind turbine interaction

A new wake surrogate model based on Reynolds-averaged Navier-Stokes (RANS) single rotor simulations is presented. The model relies on a series of three-dimensional pre-calculated deficit and added turbulence intensity flow fields, stored in a look-up table (LUT) as a function of the thrust coefficient and the ambient turbulence intensity. For any combination of these parameters, the flow around a wind turbine can be predicted by linearly interpolating within the look-up table. Furthermore, the resulting three-dimensional flow fields from different turbine sources can be superposed linearly to calculate the total wind farm flow. The model is implemented in PyWake and benchmarked against other, commonly employed engineering wake models, namely the Gaussian-Bastankhah, the N. O. Jensen and the Zong models, where RANS wind farm simulations are used as reference. In both full and partial wake cases, the surrogate model achieves a higher accuracy than any other model. Besides providing an accuracy comparable to a full RANS solution, the model can compute a flow case in the order of 1 s on a single processor. The main disadvantage is that the generation of the look-up table is time consuming, computationally expensive and can be memory demanding (especially if more inputs, such as the yaw misalignment angle, stability, etc. are added). Nevertheless, generating the LUT only has to be done once per wind turbine type.

Low-rank approximation of Hankel matrices in denoising applications for statistical damage diagnosis of wind turbine blades

Model order selection is a fundamental task in subspace identification for estimation of modal parameters, uncertainty propagation and damage diagnosis. However, the true model order and the related low-rank structure of the dynamic system are generally unknown. In this paper, a statistical methodology to actively select the dynamic signal subspace in covariance-driven subspace identification is developed on the basis of statistical analysis of the eigenvalue condition numbers of the output covariance Hankel matrix. It is shown that the condition numbers highly sensitive to random perturbations characterize the noise subspace. The signal subspace is separated from the noise subspace by analyzing two statistical parameters associated with the condition number sensitivity, whose thresholds are user-defined. A practical algorithm to retrieve the system dynamics is designed and demonstrated on a running example of a simulated wind turbine blade benchmark. The resultant framework is then applied in the context of damage detection on a medium-size wind turbine blade. It is demonstrated that the detectability of small damage is enhanced compared to the classic approaches and robustness of damage diagnosis is increased by reducing the number of false alarms.

Transient torque reversals in indirect drive wind turbines

AbstractThe adverse effect of transient torque reversals (TTRs) on wind turbine gearboxes can be severe due to their magnitude and rapid occurrence compared with other equipment. The primary damage is caused to the bearings as the bearing loaded zone rapidly changes its direction. Other components are also affected by TTRs (such as gear tooth); however, its impact on bearings is the largest. While the occurrence and severity of TTRs are acknowledged in the industry, there is a lack of academic literature on their initiation, propagation and the associated risk of damage. Furthermore, in the wide range of operation modes of a wind turbine, it is not known which modes can lead to TTRs. Further, the interdependence of TTRs on environmental loading like the wind is also not reported. This paper aims to address these unknowns by expanding on the understanding of TTRs using a high‐fidelity numerical model of an indirect drive wind turbine with a doubly fed induction generator (DFIG). To this end, a multibody model of the drivetrain is developed in SIMPACK. The model of the drivetrain is explicitly coupled to state‐of‐the‐art wind turbine simulator OpenFAST and a grid‐connected DFIG developed in MATLAB®'s Simulink® allowing a coupled analysis of the electromechanical system. A metric termed slip risk duration is proposed in this paper to quantify the risk associated with the TTRs. The paper first investigates a wide range of IEC design load cases to uncover which load cases can lead to TTRs. It was found that emergency stops and symmetric grid voltage drops can lead to TTRs. Next, the dependence of the TTRs on inflow wind parameters is investigated using a sensitivity analysis. It was found that the instantaneous wind speed at the onset of the grid fault or emergency shutdown was the most influential factor in the slip risk duration. The investigation enables the designer to predict the occurrence of TTRs and quantify the associated risk of damage. The paper concludes with recommendations for utility‐scale wind turbines and directions for future research.

Non-iterative vortex-based smearing correction for the actuator line method

The actuator line method (ALM) is used extensively in wind turbine and rotor simulations. However, its original uncorrected formulation overestimates the forces near the tip of the blades and does not reproduce well forces on translating wings. The recently proposed vortex-based smearing correction for the ALM is a correction based on physical and mathematical properties of the simulation that allows for a more accurate and general ALM. So far, to correct the forces on the blades, the smearing correction depended on an iterative process at every time step, which is usually slower, less stable and less deterministic than direct methods. In this work, a non-iterative process is proposed and validated. First, we propose a formulation of the nonlinear lifting line that is equivalent to the ALM with smearing correction, showing that the results are practically identical for a translating wing. Then, by linearizing the lifting line method, the iterative process of the correction is substituted by the direct solution of a small linear system. No significant difference is observed in the results of the iterative and non-iterative corrections, in both wing and rotor simulations. Additional contributions of the present work include the use of a more accurate approximation for the velocity induced by a smeared vortex segment and the implementation of a free-vortex wake model to define the vortex sheet, which contribute to the accuracy and generality of the method. The results presented here may motivate the adoption of the ALM by other communities, for example, in fixed-wing applications.

AI-enabled and multimodal data driven smart health monitoring of wind power systems: A case study

The development of AI has enabled the fault detection of industrial components to be achieved through the combination with deep learning. A detection method combined with deep learning has also emerged for the fault detection of fan blades, such as models based on neural networks using the appearance or sound of the blades. However, the detection model obtained from a single data type often has limitations, such as low accuracy and overfitting. This is also the problem with fan blade detection. In contrast, multimodal data fusion detection models are often more stable. The modality diversity of blade diagnosis is strong, and it can be achieved from multiple modalities such as image, sound, and vibration. To improve the accuracy of fault diagnosis of fan blades, this article proposes a multimodal double-layer detection system (MTDS) based on decision-level and feature-level fusion. The system includes a wind turbine simulation platform and a multimodal detection system. It mainly obtains different modal data of the simulated wind turbine from the image, sound, and vibration signals, including blade images through unmanned aerial vehicle photography, blade vibration signals through electronic vibrators, and blade sound signals through microphones. The highly correlated sound and vibration modal data are fused at the feature level, and a detection model based on the sound and vibration mixed mode is implemented using a sound-vibration-CNN (SV-CNN) proposed in this case. Then, a detection model of the image mode is trained based on the blade image using a Convolution Block Attention Module ResNet (CBAM-ResNet) network. Finally, the detection input of the two modal models is fed into a perceptron to obtain the final prediction result, and the decision-level fusion is implemented to achieve fan blade detection based on multimodal, namely the implementation of MTDS.

Strength Analysis on Horizontal Axis Wind Turbine Propeller Blade PVC Pipe with Angled Ends

The basic problem of appropriate wind energy technology is how to design wind turbines from materials that are easily available on the market, one solution is PVC pipe as the blade material. For this reason, it is necessary to analyze the working stress that occurs in the blade construction, so that the PVC pipe propeller wind turbine is safe when applied in society. The purpose of this study was to determine the effect of wind speed and tip elbow width on working stress. The simulation test method uses SolidWorks Flow Simulation Software and then the results are exported to Static Simulation to determine the strength of the material. Simulation tests were carried out with wind loads on PVC pipe propellers with wind speeds of 5 m/s, 6 m/s, and 7 m/s and elbow tip widths of 100 mm, 110 mm, and 130 mm. The results of the maximum stress value in the wind turbine simulation test with the addition of an elbow tip were obtained at a wind speed of 7 m/s and an elbow tip width of 130 mm

Study of air compressibility effects on the aerodynamic performance of the IEA-15 MW offshore wind turbine

With the gradual upscaling of offshore wind turbines, the blade size becomes large and the blade tip velocity reaches almost a Mach number of 0.3, the limit of the incompressible flow assumption.To simulate wind turbine flows, an incompressible solver was often a good choice as it gave good predictions and the Mach number of the wind turbine flows were small. When the Mach number is increased to be close to 0.3, the validity of incompressible flow may be questionable and thus needs to be checked. In this paper, an accurate wind turbine flow solution method is proposed to study the compressibility effects. First, the National Renewable Energy Laboratory (NREL) Phase VI wind turbine is used as an example to verify the method at a small Mach number. Through a comparative analysis between the compressible, the incompressible numerical results, and experimental data, the proposed method is found with a good simulation accuracy. Next, the flow fields of the large wind turbine IEA-15 MW, under different wind conditions are simulated. The local Mach number, density and pressure coefficient at different blade cross-sections of the compressible results are analyzed and compared to its incompressible ones, and the influences of compressibility on the thrust, torque and power of the wind turbine are quantified. The results show that at the rated wind speed, the thrust of the compressible flow simulation is 1.40 % higher than that of the incompressible one, and the torque of the compressible flow simulation is nearly 11.07 % higher than that of the incompressible one. As a result, the compressibility effects are recommended to be added in future studies of large wind turbines.

Verification and validation of CFD simulations of the NTNU BT1 wind turbine

Verification and validation of CFD simulations of the NTNU BT1 wind turbine

Wind turbine emulator control improvement using nonlinear PI controller for wind energy conversion system: Design and real‐time implementation

SummaryWind turbine emulators (WTE) have become a necessity for testing, developing, and improving design and control strategies in the renewable energy domain. The aim of this paper is to realize an experimental standalone wind energy conversion system emulator (WECSE) with improved torque and current control strategy using a nonlinear PI controller. The prototype was developed with a separately excited DC motor to simulate the wind turbine by providing the required speed and torque for power generation using a directly driven wound‐rotor synchronous generator and a power conversion system controlled by a modified drift‐free Perturb and Observe (P&O) Maximum Power Point Tracking algorithm (MPPT). The DC motor torque is controlled by an nonlinear PI controller regulator for an estimated current reference through a chopper driven by a dSPACE control board where the MATLAB/Simulink platform is used for wind turbine simulation. The proposed method was validated by experimental tests for different wind speeds and was compared with the conventional method. The experimental results have demonstrated that the control, emulation, and MPPT performances of the proposed method are significantly better.

A comparison of dynamic inflow models for the blade element momentum method

Abstract. With the increase in rotor sizes, the implementation of innovative pitch control strategies, and the first floating solutions entering the market, the importance of unsteady aerodynamic phenomena in the operation of modern offshore wind turbines has increased significantly. Including aerodynamic unsteadiness in blade element momentum (BEM) methods used to simulate wind turbine design envelopes requires specific sub-models. One of them is the dynamic inflow model, which attempts to reproduce the effects of the unsteady wake evolution on the rotor plane induction. Although several models have been proposed, the lack of a consistent and comprehensive comparison makes their relative performance in the simulation of large rotors still uncertain. More importantly, different dynamic inflow model predictions have never been compared for a standard fatigue load case, and thus it is not clear what their impact on the design loads estimated with BEM is. The present study contributes to filling these gaps by implementing all the main dynamic inflow models in a single solver and comparing their relative performance on a 220 m diameter offshore rotor design. Results are compared for simple prescribed blade pitch time histories in uniform inflow conditions first, verifying the predictions against a high-fidelity free-vortex-wake model and showing the benefit of new two-constant models. Then the effect of shed vorticity is investigated in detail, revealing its major contribution to the observed differences between BEM and free-vortex results. Finally, the simulation of a standard fatigue load case prescribing the same blade pitch and rotor speed time histories reveals that including a dynamic inflow model in BEM tends to increase the fatigue load predictions compared to a quasi-steady BEM approach, while the relative differences among the models are limited.

Numerical Analysis of Solar-Wind Hybrid Power Generation System

The Solar and wind energy produce fluctuated output energy when used individually and does not ensure the base size of power continuously required by the center of load. There is a necessity of hybridization of energy sources that is feasible in terms of efficiency and economy. The combination of solar with wind energy is one of the best proven technology either with battery mode or stand alone grid connection. Benefits of utilizing hybrid solar wind turbine are manifold This paper focusses on the designing of hybrid solar wind turbine system for the power generation from solar and wind renewable sources for household purpose in the remote areas that are connected to grid. An investigation is done on the solar and wind energy harness in a required geographic space’s weather data collection of solar radiation and wind speed at respective location from India. Numerical analysis of hybrid solar wind turbine, was conducted with separate standalone system due to the constraint of simulation tool. Simulations of Wind Turbine is done by computational fluid dynamics (CFD) that is found based on velocity of wind. The simulated result which is converted from kinetic form of mechanical energy that converted to electrical energy using analytical formulas. The data for simulation was collected from National thermal power corporation, Ramagundam , Indian Meteorological Department.

Coupling turbulent flow with blade aeroelastics and control modules in large-eddy simulation of utility-scale wind turbines

We present a large-eddy simulation framework capable of control co-design of large wind turbines, coupling the turbulent flow environment with blade aeroelastics and turbine controllers. The geometry and aerodynamics of the rotor blades and the turbine nacelle are parameterized using an actuator surface model. The baseline collective pitch control and individual pitch control (IPC) algorithms, consisting of a single-input, single-output proportional–integral controller and two integral controllers, respectively, are incorporated into the simulation framework. Furthermore, a second-order model based on the Euler–Bernoulli beam theory is implemented to describe the blade deformation. Simulations are carried out to investigate the impact of collective and individual pitch control strategies on the deflection of turbine blades. Our results show that the IPC reduces the blade tip deflection fluctuations in the out-of-plane direction, while the fluctuations of the blade tip deflection along the in-plane direction are barely affected by the IPC. Furthermore, the blade out-of-plane deformation fluctuation is underestimated by the one-way coupling approach compared to the two-way coupling approach. The findings of this study reveal the importance of advanced control systems in reducing the dynamic loads on wind turbine blades and underscore the potential of control co-design to reduce the levelized cost of wind energy.

Platform Oscillation Reduction of a Floating Offshore Wind Turbine

This paper focuses on the design of an individual blade pitch controller to reduce the platform oscillation of a floating offshore wind turbine with repositioning capacity. Such reduction is helpful for captured power regulation in wind farm control via turbine repositioning. In this study, a baseline 5MW wind turbine on a semi-submersible platform with long mooring lines is used for demonstration purposes. The model for the controller design is obtained as a state equation using the linearization functionality of the wind turbine simulator OpenFAST, activating only platform pitch and platform yaw as degrees of freedom. Based on the model, a linear quadratic regulator (LQR) is designed for platform vibration suppression. During each revolution, the controller prioritizes producing restoring moments to address platform pitch oscillation as the blades approach the vertical centerline of the rotor plane. Conversely, as the blades rotate close to the horizontal centerline of the rotor plane, the controller shifts its focus towards generating restoring moments to counteract platform yaw fluctuations. It is demonstrated in OpenFAST that the designed LQR-based individual blade pitch controller effectively reduces platform surge, roll, pitch, and yaw oscillation, resulting in improved power regulation during turbine repositioning.

Causality-Free Modeling of a Floating Wind Turbine Semisubmersible Platform with Validation Results

This paper presents an acausal modeling approach for developing a hydrodynamic module in the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS), a wind turbine simulation tool being developed by the authors, to facilitate control co-design of floating offshore wind turbines (FOWTs). The available data of the semi-submersible VolturnUS-S FOWT is incorporated into the modeling, simulation, and control demonstrations. The model is verified and validated using numerical data from industrial-standard simulation platform OpenFAST and experimental data from the Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) Project. Numerical results demonstrate that the hydrodynamic module in CRAFTS can qualitatively capture loads and responses from the free decay tests, as well as the stabilizing effects of the tuned mass dampers (TMDs), which are tuned to attenuate the platform pitch resonance or the tower bending resonance.

Stabilization of the Wind Turbine Floating Platform using Mooring Actuation

In this study, a wind turbine spar-buoy floating platform is modeled in the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS), a comprehensive wind turbine simulation tool being developed by the authors, to investigate mooring actuation for stabilizing the surge and pitch motions. The model is validated against the industrial-standard simulator OpenFAST. A reduced-order model of the platform is developed using a mass-spring-damper system (M-K-C system), and the system parameters are estimated. Optimal LQR control gains are obtained for the reduced-order model, and the required actuation forces are calculated using these gains. A control allocation matrix is used to represent the relation between the necessary cable tensions and the required actuation forces from the control system. The performance of the mooring actuation is tested under various load cases: initial perturbations and different sea state conditions with irregular waves. Simulation results demonstrate that surge motion is significantly reduced with moderate changes in cable lengths in both load cases while controlling pitch motion requires higher changes in cable length and is challenging to control under irregular wave conditions.

Data-Driven and Model-Based Control Techniques for a Wind Turbine Benchmark Model

Abstract: Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high–fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Extended simulations with the wind turbine benchhmark model and the Monte–Carlo tool represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model–reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.

Assessment through high-fidelity simulations of a low-fidelity noise prediction tool for a vertical-axis wind turbine

Vertical-axis wind turbines have the potential to be installed nearby urban areas, where noise regulations are a constraint. Accurate modelling of the far-field noise with low-order fidelity methods is essential to account for noise early in the design phase. The challenge for the vertical-axis wind turbine is the unsteady azimuthal variation of the flow over the blades, which makes the prediction of the far-field noise complex with low-fidelity methods. In this paper, the state-of-the-art of low-fidelity methods are assessed against scale-resolving high-fidelity numerical simulations of a realistic vertical-axis wind turbine carried out with the lattice-Boltzmann very large eddy simulations method. High-fidelity numerical data are validated against experimental aerodynamics data of the same vertical-axis wind turbine. The low-fidelity method is based on the actuator cylinder model coupled with semi-empirical models for airfoil-self noise and turbulence-interaction noise. Results show a good agreement between the high-fidelity simulations and the low-fidelity model at low frequencies (i.e. between 2 × 101Hz and 1 × 102Hz), where turbulence-interaction noise is the dominant noise source. At higher frequencies, the airfoil-self noise dominates and existing methods, based on steady airfoils, do not correctly predict noise. This paper shows that the presented low-fidelity model predicts the aerodynamics and the aeroacoustics of the turbine with an acceptable accuracy for a design stage. However, improvements are needed to better predict the far-field noise for blades in an unsteady field.

Effects of Atmospheric Icing on Performance of Controlled Wind Turbine

Icing deteriorates the performance of wind turbine rotors by changing the blade airfoils’ shapes. It decreases the lift, increases the drag, and subsequently causes power production losses and load increase on turbines’ structures. In the present study, the effects of atmospheric icing on the performance of a controlled large-scale wind turbine is estimated through simulations. To achieve the target, the MS (Mustafa Sahin) Bladed Wind Turbine Simulation Model is used for the analyses of the National Renewable Energy Laboratory (NREL) 5 MW turbine with and without iced blades. Icing modeling is realized based on its main characteristics and its effects on blade aerodynamics. Turbine performance estimations are carried out at various uniform wind speeds between cut-in and cut-out wind speeds and are presented in terms of various turbine parameters such as power, thrust force, blade pitch angle, and rotor speed. Simulation evaluations show that even a light ice accretion along the blades varies the turbine characteristics and dynamics, changes the cut-in and rated wind speeds, and affects the aforementioned turbine parameters differently in the below and above rated regions.

Parked aeroelastic field rotor response for a 20% scaled demonstrator of a 13‐MW downwind turbine

AbstractAeroelastic parked testing of a unique downwind two‐bladed subscale rotor was completed to characterize the response of an extreme‐scale 13‐MW turbine in high‐wind parked conditions. A 20% geometric scaling was used resulting in scaled 20‐m‐long blades, whose structural and stiffness properties were designed using aeroelastic scaling to replicate the nondimensional structural aeroelastic deflections and dynamics that would occur for a lightweight, downwind 13‐MW rotor. The subscale rotor was mounted and field tested on the two‐bladed Controls Advanced Research Turbine (CART2) at the National Renewable Energy Laboratory's Flatiron Campus (NREL FC). The parked testing of these highly flexible blades included both pitch‐to‐run and pitch‐to‐feather configurations with the blades in the horizontal braked orientation. The collected experimental data includes the unsteady flapwise root bending moments and tip deflections as a function of inflow wind conditions. The bending moments are based on strain gauges located in the root section, whereas the tip deflections are captured by a video camera on the hub of the turbine pointed toward the tip of the blade. The experimental results are compared against computational predictions generated by FAST, a wind turbine simulation software, for the subscale and full‐scale models with consistent unsteady wind fields. FAST reasonably predicted the bending moments and deflections of the experimental data in terms of both the mean and standard deviations. These results demonstrate the efficacy of the first such aeroelastically scaled turbine test and demonstrate that a highly flexible lightweight downwind coned rotor can be designed to withstand extreme loads in parked conditions.