Wind Turbine Simulator Research Articles

Identification of aerodynamic damping matrix for operating wind turbines

Accurate knowledge of wind turbine tower vibration damping is essential for the estimation of fatigue life. However, the responses in the fore-aft and side-side directions are coupled through the wind-rotor interaction under operational conditions. This causes energy transfers and complicates aerodynamic damping identification using conventional damping ratios. Employing a reduced two-degree of freedom wind turbine model developed in this paper, this coupling can be accurately expressed by an unconventional aerodynamic damping matrix. Simulated time series obtained from this model were successfully verified against the outputs from the wind turbine simulation tool FAST. Based on the reduced system obtained, a matrix-based identification method is proposed to identify the aerodynamic damping for numerically simulated wind turbine tower responses. Applying harmonic excitations to the tower allowed the frequency response functions of the wind turbine system to be obtained and the aerodynamic damping matrix to be extracted. Results from this identification were compared to traditional operational modal analysis methods including standard and modified stochastic subspace identification. The damping in the fore-aft direction was successfully identified by all methods, but results showed that the identified damping matrix performs better in capturing the aerodynamic damping and coupling for the side-side responses.

Numerical Simulation of Wind Turbine Aerodynamic Characteristics under Wind Shear Based on Lattice-Boltzmann Method

In order to study the influence of wind shear on the aerodynamic characteristics of large wind turbines, taking the 5MW wind turbine blade model published by NREL as the research object, large eddy simulation (LES) of wind turbines was carried out by using XFlow fluid simulation software based on Lattice-Boltzmann method (LBM). WALE turbulence model was used to study wind shear at 3, 11.2 and 25m/s wind speeds. The effect of factors on the axial thrust and torque of wind turbines is compared with the data published by NREL. The results show that the XFlow software based on LBM and LES method has good capturing ability for the eddy wake of wind turbine; wind shear causes the airfoil section of each section of blade to deviate from the best designed attack angle in theory and results in a decrease in torque applied to the wind turbine.

Large eddy simulation of wind turbine wakes considering control algorithm and Coriolis force

Large eddy simulation of wind turbine wakes considering control algorithm and Coriolis force

Aeromechanical Analysis of a Complete Wind Turbine Using Nonlinear Frequency Domain Solution Method

Abstract The high-fidelity computational fluid dynamics (CFD) simulations of a complete wind turbine model usually require significant computational resources. It will require much more resources if the fluid–structure interactions (FSIs) between the blade and the flow are considered, and it has been the major challenge in the industry. The aeromechanical analysis of a complete wind turbine model using a high-fidelity CFD method is discussed in this paper. The distinctiveness of this paper is the application of the nonlinear frequency domain solution method to analyze the forced response and flutter instability of the blade as well as to investigate the unsteady flow field across the wind turbine rotor and the tower. This method also enables the aeromechanical simulations of wind turbines for various interblade phase angles in a combination with a phase shift solution method. Extensive validations of the nonlinear frequency domain solution method against the conventional time domain solution method reveal that the proposed frequency domain solution method can reduce the computational cost by one to two orders of magnitude.

Performance Simulation of Wind Turbine with Optimal Designed Trailing-Edge Serrations

Performance Simulation of Wind Turbine with Optimal Designed Trailing-Edge Serrations

Large eddy simulations of wind turbine wakes in typical complex topographies

AbstractThere is a need to clarify the coupling characteristics of terrain‐induced wind fields and wind turbine‐induced wake in wind farm micrositing. However, research investigating the effect of hill shape on this interaction is lacking. In addition, during the optimization of the layout of the turbines over topographies, the flow behind the turbines should be predicted in a fast way. After obtaining the wake flow of the turbine mounted on flat terrain and the flow over the topographies, there are mainly two superposition methods to predict the turbine wake flow over the topographies. One is to add the wind deficit following the location with a vertical distance of the hub height (D‐line). The other is to add the wind deficit following the streamline starting from the turbine center (B‐line). It remains unknown to what extent these two superposition methods can be adopted. Therefore, the effects of hill shape, wind turbine size, and turbine location are investigated. When the wind deficit, obtained from modeling the wake flow of the turbine mounted on flat terrain, is superposed following B‐line, the results are overall better than those when following D‐line.

Aeroelastic numerical simulation of a magnetically levitated horizontal axis wind turbine

This paper presents mathematical modeling of direct drive wind turbines with a three-point suspension magnetically levitated drivetrain. An aeroelastic numerical simulation is performed using OpenFAST software. A 10 kw small wind research turbine (SWRT) is chosen as a preliminary step in the development of a general reliable magnetically levitated drivetrain model for wind turbine (WT) simulations. This model adds an additional five degrees of freedom (DOF) to the current version of OpenFAST V2.1.0 and aims to provide more extensive studies of the application of magnetic bearing (MB) on WTs, which is the main objective of this work. The analytical design of the magnetic levitation system for WTs under study is considered. The dynamic equations of OpenFAST are redeveloped using Kane’s method for the flexible multi-body motion to include the levitated shaft dynamics. The inherent insatiability of the MB system is overcome with a robust Q-parameter model-based controller. The new dynamic equations of the MB are verified under different wind scenarios to prove the ability of MB to compensate for different aerodynamic and gravitational loads. The simulation results show that MB technology is a promising approach that can help to mitigate the WT’s vibrations and solve the current mechanical bearing problems.

Development of a wind turbine simulator to design and test micro HAWTs

The development of a micro wind turbine simulator is presented in the current study. The simulator is employed to test and assess the design and the performance of micro horizontal axis wind turbines (HAWT). These turbines can be used as micro wind turbines being utilized for household applications. The main system consists of a wind simulator, models of rotor blades, a tower model with a nacelle at the top. In this study, nacelle comprises a low-power step motor directly coupled with the turbine’s axis at its input and a designed circuit at its output to measure the generated power. As an innovative part of the simulator, the fan of the simulator is mounted within a guiding slide which can enable the user to change the yaw angle while maintaining the same distance from the HAWT. To calibrate the simulator, the results obtained from experimental investigations (i.e. wind simulator) were compared with BEM theory, CFD simulation as well as wind tunnel measurements. In addition, different conditions including yawed rotor and rotors with blades extending from the uniform inflow of the fan are experimentally assessed. Overall, the results show satisfactory response of the system in reproducing the characteristics of a given micro turbine at various conditions particularly when the tip speed ratio is close to the design value.

Nonlinear frequency domain solution method for aerodynamic and aeromechanical analysis of wind turbines

The aerodynamic simulations of wind turbines are typically carried out using a steady inflow condition. However, the aerodynamics and aeroelasticity of wind turbine blades can be significantly affected by inflow wakes due to the environmental conditions or the presence of neighbouring wind turbines. In this paper, the effects of flow unsteadiness on the aerodynamics and aeroelasticity of the wind turbine rotor are investigated. It is found that the unsteadiness of the wake can have an impact on the aerodynamic flow field around the wind turbine rotor and it could also influence the aeroelasticity of the wind turbine. One of the distinctive features of this paper is the application of the highly efficient nonlinear frequency domain solution method for modelling harmonic disturbances for the aerodynamic and aeromechanical analysis of wind turbines. A test case wind turbine is selected for the aerodynamic and aeromechanical analysis as well as for the validation of the method used. The effects of different material properties along with a large vibration amplitude on the aeroelasticity parameter known as aerodynamic damping of the wind turbine blade are also investigated in the present work. Compared to the conventional time domain solution methods, which require prohibitively large computational cost for modelling and solving aerodynamics and aeroelasticity of wind turbines, the proposed frequency domain solution method can reduce the computational cost by one to two orders of magnitude.

Requirements for Validation of Dynamic Wind Turbine Models: An International Grid Code Review

Wind power is positioned as one of the fastest-growing energy sources today, while also being a mature technology with a strong capacity for creating employment and guaranteeing environmental sustainability. However, the stochastic nature of wind may affect the integration of power plants into power systems and the availability of generation capacity. In this sense, as in the case of conventional power plants, wind power installations should be able to help maintain power system stability and reliability. To help achieve this objective, a significant number of countries have developed so-called grid interconnection agreements. These are designed to define the technical and behavioral requirements that wind power installations, as well as other power plants, must comply with when seeking connection to the national network. These documents also detail the tasks that should be conducted to certify such installations, so these can be commercially exploited. These certification processes allow countries to assess wind turbine and wind power plant simulation models. These models can then be used to estimate and simulate wind power performance under a variety of scenarios. Within this framework, and with a particular focus on the new Spanish grid code, the present paper addresses the validation process of dynamic wind turbine models followed in three countries—Spain, Germany and South Africa. In these three countries, and as a novel option, it has been proposed that these models form part of the commissioning and certification processes of wind power plants.

Design of a robustH∞dynamic sliding mode torque observer for the 100 KW wind turbine

This article presents a novel technique for the design of a robust dynamic nonlinear observer in the H ∞ scheme for the Lipschitz nonlinear model of the wind turbine. It is a challenging problem due to the aerodynamic nonlinearity of blades. A drive train of the 100 KW wind turbine benchmark model, developed by Aalborg University and KK-electronic a/c, is conducted to exhibit the effectiveness of the proposed observer approach. The new Lipschitz constant definition for this system is expressed. Based on the new dynamic method, the Lipschitz constant is increased. Therefore, the operating region is increased. A new dynamic sliding mode observer is introduced for torque estimation in the drive train. The design methodology is the use of dynamic gain instead of static one in the sliding mode observer. The dynamic observer design offers an extra degree of freedom over the classical static gain observer. We established the conditions for the suggested dynamic observer stability. The proposed approach provides the observer robustness against nonlinear uncertainties due to the maximizing the Lipschitz constant. Moreover, the design procedure with the effect of system and sensor noises is considered. Results illustrate the advantage of this work in comparison with other observers. Finally, the results are evaluated with the wind turbine simulator software FAST. • The paper studies a new robust sliding mode observer for the nonlinear wind turbine Drivetrain. • Based on the extra degree of freedom the operating region of the wind turbine has been enlarged. • The goal is to obtain a filter to stabilize the error dynamics without loss of performance. • Another contribution is improving the observer behavior by attenuating noise. • To validate the model, the drivetrain model was tested in FAST wind turbine software.

Generation and decay of counter-rotating vortices downstream of yawed wind turbines in the atmospheric boundary layer

Abstract

Recovery of energy losses using an online data-driven optimization technique

This paper investigates the energy loss due to rotor aging for a wind turbine and its recovery. Energy loss for a wind turbine is caused by formation of dust and bugs, and corrosion and erosion of the surface of the rotor by sand and rain. We present a real-time data-driven optimization algorithm that uses dither and demodulation signals to recover the energy loss by extracting online the sensitivity of the function of interest to optimize. We use a viscid–inviscid model to represent aerodynamic performance loss of the rotor due to aging. We employ time-domain aeroservoelastic simulation of the CART3 wind turbine of the National Renewable Energy Laboratory to provide a comprehensive assessment of aging and its recovery. We also investigate the impact of aging on structural loads and levelized cost of energy. Using annual energy production and WindPACT cost models of the National Renewable Energy Laboratory, the levelized cost of energy enables an overall assessment of aging and its recovery. To evaluate the impact of the energy loss recovery on structural loading, ultimate and fatigue loads for power production design load case are used. The results of this study show 6.9% reduction in the annual energy production due to aging for a class C wind condition based on IEC61400 standard. This energy loss increases the levelized cost of energy by 7.5%. Our online optimization algorithm can recover 1.7% of the energy losses, and it results in 2.0% reduction in the levelized cost of energy. Results of the ultimate loads indicate that an aged rotor reduces structural loading on most components except the main shaft where the bending moment shows an increase of 5.3%. Rotor aging also reduces the fatigue loads in most components except the tower bottom fore-aft moment with an increase of 5.5%. The statistical inference of the results shows that the proposed optimization algorithm is effective in recovering aging related energy losses of wind turbines with a confidence level of 84% based on the sampled data in this study.

A robust methodology for predicting extreme structural responses of offshore wind turbines

ABSTRACT This paper proposes a robust methodology for predicting extreme structural responses of offshore wind turbines. This robust methodology starts with forecasting an improved IFORM (Inverse-First-Order Reliability Method) environmental contour line through the use of principal component analysis. It then performs stochastic time domain simulations of an offshore wind turbine based on the information of the highest sea state identified along the aforementioned environmental contour line. Next, an enhanced Peaks-Over-Threshold (POT) method is utilised for fitting an extreme value distribution based on which a long-term extreme structural response can finally be obtained. A specific example of predicting the 50-year extreme structural responses of a monopile-supported 5MW offshore wind turbine will be provided in this paper for demonstrating the robustness of our proposed methodology.

A general substructure-based framework for input-state estimation using limited output measurements

This paper presents a general framework for estimating the state and unknown inputs at the level of a system subdomain using a limited number of output measurements, enabling thus the component-based vibration monitoring or control and providing a novel approach to model updating and hybrid testing applications. Under the premise that the system subdomain dynamics are driven by the unknown (i) externally applied inputs and (ii) interface forces, with the latter representing the unmodeled system components, the problem of output-only response prediction at the substructure level can be tailored to a Bayesian input-state estimation context. As such, the solution is recursively obtained by fusing a Reduced Order Model (ROM) of the structural subdomain of interest with the available response measurements via a Bayesian filter. The proposed framework is without loss of generality established on the basis of fixed- and free-interface domain decomposition methods and verified by means of three simulated Wind Turbine (WT) structure applications of increasing complexity. The performance is assessed in terms of the achieved accuracy on the estimated unknown quantities.

URANS simulations of a horizontal axis wind turbine under stall condition using Reynolds stress turbulence models

Over the last decade, a dramatic increase in the size of commercial wind turbines is noticeable. The optimal structural design and reliable fatigue-life prediction of these large-scale structures depend on the accurate modeling of the turbulent flow around the rotors. The present paper aims at extending the knowledge of the turbulent flow characteristics around horizontal axis wind turbines and assessing the performance of several URANS turbulence models, principally Reynolds stress turbulence (RST) models, in predicting the wind turbine aerodynamics under stall condition. The simulations are performed using the NREL phase VI wind turbine over a wide range of wind speeds. Three RST models and the linear and quadratic variants of the k−ω SST turbulence model are examined. The results demonstrate that the RST models generally provide more reliable predictions. An evaluation of the Boussinesq hypothesis questions the applicability of the turbulence models employing this hypothesis to the wind turbine aerodynamic problems. Finally, the elliptic blending RST model, which is one of the latest formulations of the RST models, appears to provide the best trade-off between accuracy and computational cost.

Large-eddy simulation of wind turbines immersed in the wake of a cube-shaped building

Motivated by the potential of wind power based electricity generation modules in urban environments, flow properties of wind turbines operating behind a building-like wall-attached cube are investigated through large-eddy simulation. Significant power losses with increased power fluctuations are observed for the first turbine downstream of the cube. Also, the power losses and fluctuations increase with decreasing distance to the cube. However, a faster recovery of the turbine wake is observed, due to not only enhanced turbulent transport but also due to convection associated with the secondary mean flow structure behind the cube. The transport of mass, momentum and energy fluxes shows that turbines at different distances receive mean kinetic energy from different layers of air motion upstream of the cube. Associated transport tubes exhibit deflection towards to the ground behind the first turbine due to the mean flow’s downwash, which can significantly reduce the sheltering effect of turbines at further downstream locations. Therefore, when a second turbine is placed behind the first turbine, the second turbine can produce more power than in the same setting without the cube. The total power output of two turbines behind a cube can be even larger than that without the cube, in certain cases.

Cross-correlation-based approach to align turbulent inflow between CFD and lower-fidelity-codes in wind turbine simulations

In cases with turbulent inflow, the analysis of the temporal development of forces could provide more insight into differences in calculated fatigue loads of wind turbines. While lifting-line-codes and the Blade-Element-Momentum (BEM) approach do not resolve the inflow, Computational Fluid-Dynamic (CFD) codes resolve the entire flow field. A comparison of time series between the different codes therefore requires a consistent input of the background turbulence. This was enabled by extracting the turbulent velocity field from empty box (without rotor) CFD simulations at the anticipated rotor position. The presence of a rotor in the CFD simulations leads to a delay in the inflow due to the induced velocity. This blockage effect of the rotor was quantified by a cross-correlation. The velocity field extracted from the simulation of the empty box was shifted by the resulting temporal offset before it was used as lifting-line-code or BEM input. Thus, a time-dependent load comparison between the codes could be performed. It was found that the difference in load predictions between CFD and BEM seems to be larger at peak values. For cases with high thrust coefficient or high turbulence intensity, a simpler analytical approach resulted in significantly higher temporal offsets than the cross-correlation.

Biomimetic individual pitch control for load alleviation

Individual pitch control has shown great capability of alleviating the oscillating loads experienced by wind turbine blades due to wind shear, atmospheric turbulence, yaw misalignement or wake impingement. This work presents a bio-inspired structure for individual pitch control where neural oscillators produce basic rhythmic patterns of the pitch angles, while a deep neural network modulates them according to the environmental conditions. This mimics, respectively, the central patterns generators present in the spinal chord of animals and their cortex. The mimicry further applies to the neural network as it is trained with reinforcement learning, a method inspired by the trial and error way of animal learning. Large eddy simulations of the reference NREL 5MW wind turbine using this biomimetic controller show that the neural network learns how to reduce fatigue loads by producing smooth pitching commands.

Towards the development of a wake meandering model based on neural networks

In this work, we develop a neural network model for predicting the instantaneous wake position, which is crucial for a wake meandering model. The data used for training are from the large-eddy simulation of a utility-scale wind turbine. A neural network of four hidden layers with 128 units for each layer is found to be effective when training the model. Effects of different input features on the accuracy of the trained model are systematically tested. It is found that the input features including the downwind and crosswind velocities at two locations upwind of the turbine and the thrust and torque acting on the turbine are enough to guarantee the accuracy of the trained model. Without using the thrust and torque as the input features, the accuracy of the model is significantly worse.