Wind Turbine Simulator Research Articles

Combined genetic algorithm and response surface methodology‐based bi‐optimization of a vertical‐axis wind turbine numerically simulated using CFD

AbstractIn this study, computational fluid dynamic (CFD) simulation of a vertical axis wind turbine (VAWT) geometry based on the Unsteady Reynolds–Averaged Navier–Stokes equations was investigated. In addition, the relationship between the geometric parameters of the VAWT and the two response variables, that is, moment and lift force, was determined using response surface methodology (RSM). Then, the Non‐Dominated Sorting Genetic Algorithm (NSGA‐II) was used to solve the multi‐objective optimization problem. The results obtained from the RSM showed that the lift force of the turbine is more sensitive to the change in the blade chord length, and the output moment of the turbine is more sensitive to the change in the rotor radius. Using the NSGA‐II multi‐objective optimization algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, it was determined that among the optimal values of the independent variable, the most optimal response occurs in blade chord length = 0.18 m, rotor radius = 0.4 m, blade pitch angle = −3.27° and number of blades = 4. In these optimal values of the independent variables, the values of the dependent variables, which included the turbine's moment and the blades’ lift force, were obtained as 9.58 N m and 57.89 N, respectively.

High-Precision Numerical Investigation of a VAWT Starting Process

For both conventional and renewable energy conversion processes, computational fluid dynamics (CFD) has been used to address more energy-related challenges in recent decades. Using CFD to investigate vertical-axis wind turbines has become more common in recent years. The main goals of this application have been to more accurately predict the turbine’s performance and to comprehend the complicated nature of the complex turbulent flow. The vertical-axis wind turbine (VAWT) simulation for energy-generating applications has several intricate components. One of them is the study of the chaotic flow that occurs during the first stages of the starting process, and which greatly influences overall effectiveness. In this article, the performance of the wind turbine was increased using a passive flow control approach. The numerical research was carried out using Large Eddy Simulation for four alternative tip speed ratios in both cases, the classic and the optimized case, equipped with a vortex trap on the extrados of the blades. The power and torque coefficient variations, as well as the velocity magnitude contours, show that the starting process may begin with a significant improvement in efficiency when flow control is used.

Assessing wind turbine blade durability longevity utilizing national renewable energy laboratory tools

With the escalating significance of renewable energy, there exists a pressing demand for precise software and tools capable of designing and forecasting wind turbine blade service life. OpenFAST, TurbSim, and MLife are pivotal open-source wind turbine simulation tools that integrate aerodynamics, structural dynamics, wind simulation, and control systems. They enable accurate prediction of wind turbine performance. This study aims to leverage these software resources to model turbulent wind conditions using predefined basic parameters and then calculate fatigue and longevity of the wind turbine blade to determine service life. Particularly, MLife was employed for rose loading, enhancing the fidelity of the loading cycle simulation. Collaboration between the National Renewable Energy Laboratory and the research team played a crucial role in establishing a foundational baseline and implementing realistic input parameters for evaluating the ultimate load, determining damage equivalent loads (DEL), and projecting service life. In all simulations, a constant factor of safety (FOS) of 1.5 was consistently applied. Additionally, Finite Element Analysis (FEA) was employed to validate our numerical experiments, ensuring the accuracy of the obtained results by correlating simulation outcomes with real-world scenarios, further strengthening the credibility of the study.

Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison

Abstract. Uncertainty quantification (UQ) is a well-established category of methods to estimate the effect of parameter variations on a quantity of interest based on a solid mathematical foundation. In the wind energy field most UQ studies focus on the sensitivity of turbine loads. This article presents a framework, wrapped around a modern Python UQ library, to analyze the impact of uncertain turbine properties on aeroelastic stability. The UQ methodology applies a polynomial chaos expansion surrogate model. A comparison is made between different wind turbine simulation tools on the engineering model level (alaska/Wind, Bladed, HAWC2/HAWCStab2, and Simpack). Two case studies are used to demonstrate the effectiveness of the method to analyze the sensitivity of the aeroelastic damping of an unstable turbine mode to variations of structural blade cross-section parameters. The code-to-code comparison shows good agreement between the simulation tools for the reference model, but also significant differences in the sensitivities.

Analyzing and Validating Energy Performance through Computational Simulation of a Helical Vertical Axis Wind Turbine

Analyzing and Validating Energy Performance through Computational Simulation of a Helical Vertical Axis Wind Turbine

Unsteady numerical simulation of wind turbine with bio-inspired wing-tip modification

This study evaluates the effects of a novel winglet design on the aerodynamics of the 10 MW Denmark Technical University wind turbine. The unsteady Reynolds-averaged Navier–Stokes (URANS) and the detached eddy simulation (DES) are used to numerically simulate the physics of both the baseline turbine (i.e., no winglet included) and a wingletted turbine under the rated operating condition. The results show that the addition of the winglet alters both the structure of the wing-tip vortex and the vorticity distribution in the wake, leading to lower levels of average vorticity. Moreover, the wingletted wind turbine increases the torque of the turbine by 6.3% while only increasing the drag by 2.5%. Although the URANS formulation performs well at calculating the power and force distribution at the turbine, it falls short of providing an accurate description of the flow field of the wake, failing to calculate the unsteady scales captured by the DES model.

A prediction method for blade deformations of large-scale FVAWTs using dynamics theory and machine learning techniques

There is renewed interest in floating vertical axis wind turbines (FVAWTs) as offshore wind turbines progressively increase in size and move into deeper waters. To explore the potential of large-scale FVAWTs for future commercialization, it is crucial to investigate blade deformations using an accurate and effective method. In this study, we developed a hybrid model, namely, the SVST-ANN, which integrates dynamic theory and machine learning techniques to predict blade deformations. Specifically, an artificial neural network (ANN) module is incorporated into the slack coupled vertical axis wind turbine simulation tool (SVST), which significantly reduces the total computational time. A comparative study was conducted between the SVST-ANN model and the traditional SVST model, employing a 10 MW helical-type FVAWT as an example. The results show that the SVST-ANN model can accurately and efficiently predict blade deformations. The maximum errors for the maximum value, average value, and standard deviation across all nodes are minimal, with a corresponding computational time reduction of approximately 60 %. This study provides a novel method for investigating the dynamic behavior of the FVAWTs, which is more effective for calculating the elastic deformations of blades than traditional numerical methods.

Wind Potential Assessment for Songkhla, Thailand

The analysis and evaluation of wind energy projects are important to understand their economic and environmental suitability for installation and operation. Using wind data from the Meteorological Department, Used WAsP software for calculating, simulating, and analyzing the Annual Energy Production (AEP) and then applied it to calculate the Levelized Cost of Electricity (LCOE) of wind turbines installed in the Songkhla province area. The selected areas are suitable for all three models of wind turbines in the simulation. From the wind data analysis, wind direct was found that in the east sector (sector 4), there is the highest wind frequency at the wind station. The simulation results from Laem son-on area and Hua khao area show suitable mean wind speeds for wind farm installations. In the wind turbine simulation, three models were compared: Bonus 300 kW MkIII, Bonus 1.3 MW, and PowerWind 56 900 kW. At the Songkhla cape area, the positions with the highest AEP were 132.485 MWh, 344.419 MWh, and 332.597 MWh, respectively. Hua Khao area, the positions with the highest AEP were 225.284 MWh, 586.303 MWh, and 540.045 MWh, respectively. In the LCOE calculations for all model of wind turbines, at both Laem Son- On and Hua Khao locations, the most cost-effective wind turbine is the Bonus 300 kW. It has an LCOE of $142.43/MWh and $83.76/MWh, respectively. Therefore, the most cost-effective location is Hua Khao.

Tuning the Actuator Line Method to Properly Modelling Tip Effects in Finite-Length Blades

The Actuator Line Method (ALM) is gaining popularity in wind turbine simulations, as it can better handle some of the challenging operating conditions experienced by modern machines, such as highly turbulent inflows, severe aero-elastic forcing, and complex rotor-to-rotor interactions. However, it still falls behind other medium-fidelity methods such as the Lifting Line Free Vortex Wake (LLFVW) when it comes to resolving tip vortices and their effect on the blade spanwise load profile. The reason for such behavior is still unclear. A recent study suggested that this issue can be solved by reducing the scale of the angle of attack (α) sampling and force insertion towards the tip, without the need of additional corrections. This study builds on these findings to further investigate how the ALM base formulation - in terms of α sampling and force insertion - can be tuned to properly describe tip effects. An in-house ALM tool was employed to simulate a finite, constant-chord, NACA0018 wing, for which high-fidelity blade-resolved CFD (BR-CFD) data are available as benchmark. In the first part of the work, different strategies are outlined, including a novel approach for the de-coupling of the angle of attack sampling step from the force projection one, here called DE-coupled LineAverage (DELA). Their accuracy and sensitivity to ALM numerical settings are assessed at a fixed wing pitch angle of 6°. The analysis is then extended to a wider range of blade pitch angles, benchmarking the new ALM formulation against BR-CFD, ALM with the Dağ and Sørensen correction, and LLFVW in terms of blade loads, tip vortex structure, and computational effort.

Deviation of drive torque and rotational speed of a wind turbine drivetrain between test bench and wind turbine simulations

Wind turbines are a major contributor to a clean and independent energy mix in the future and therefore need to have as little downtime as possible. Downtime can be minimised by increasing the robustness of the wind turbine. The drivetrain is one of the major contributors of downtime in wind turbines. One way of increasing the robustness of wind turbine drivetrains is extensive drivetrain testing and loop-back optimization of the design and control. On the drivetrain test bench torque and other wind loads are applied. To ensure that the drivetrain reaction to the loads is the same as of the erected wind turbine the accuracy of the application of the loads needs to be sufficient. Only if the reaction loads of the drivetrain are similar to the rotor loads of the erected wind turbine a robustness increase can be achieved via the loop-back optimization after the tests. This paper therefore quantifies the deviations occurring in torque and rotational speed of the hub between the erected wind turbine and the test bench for a specific wind turbine. To do so the results of a test bench simulation are compared to results of an aerodynamic simulation of the wind turbine. For the investigated wind turbine drivetrain, the deviation in drive torque increases slightly with higher windspeeds. The torque values are maximum 2 % higher at the wind turbine compared to the rated torque. The rotational speed values are represented very well regarding the time series as well as the occurring frequencies. The speed values deviate maximum 0.5 % compared to the rated speed. The deviations are a result of differences in an underestimation of the drivetrain efficiency in the aerodynamic simulation and the inertia of the drivetrain on the test bench and wind turbine. Since the deviations are small the abstraction losses at the test bench regarding torque and speed are acceptable.

Further improvements to the double-Gaussian wake model

In onshore wind farms, the turbine-to-turbine distance can be in the order of three diameters or less. In these circumstances, traditional wake models, developed for the far wake region, lose accuracy. The double-Gaussian wake model is an approach to extend algebraic wake modelling to the near wake region, where the wake is not yet self-similar. In this work, the double-Gaussian wake model is advanced by performing large eddy simulations of a reference wind turbine and a scaled wind turbine model to investigate how the thrust coefficient and the turbulence intensity influence the near wake and wake recovery. Results show that in the near wake the maximum velocity deficits move towards the outer part of the rotor with an increasing thrust coefficient. Thus, a thrust coefficient dependent position of the double-Gaussian peaks is proposed. In addition, a wake expansion function including turbulence intensity and thrust coefficient is tuned. The new model proves to be capable of predicting the wake of different turbine models under various ambient conditions and operational states.

Floaters upscaling for multi-megawatt floating wind turbines

The floating wind industry requires wind turbines with increasing power ratings, which will require bigger platforms. However, few floater concepts are publicly available for numerical simulation of future wind turbines. To overcome this limit, this work proposes a fast and straightforward upscaling methodology to upscale already available floating platforms to greater wind turbine power ratings. The methodology does not aim to optimize the floater design, but it can generate realistic floater data for preliminary numerical simulations. The methodology is applied here to four floaters: a semisubmersible, a barge, a TLP and a spar. The platforms are upscaled for a 15 MW wind turbine and a specific deployment site. The upscaling methodology is adapted for each floater since some differences arise from one platform to the other. Whenever possible a comparison with already existing 15 MW substructures is proposed and commented.

Sensitivity of the Prediction of Wind Turbine Wakes to the Sub-Grid Scale Model

In a large-eddy simulation (LES) approach, the sub-grid scale (SGS) model accounts for the contribution of eddies and their fluxes whose length scales are smaller than the filter width. In wind turbine and farm simulations, different SGS models have been adopted, but their impact on turbine performance and wake prediction remains unknown for non-neutrally stable atmospheric boundary layers. Here, large-eddy simulations of an NREL–5MW wind turbine in stable atmospheric conditions are performed with six SGS models: standard Smagorinsky, Lagrangian-Averaged Scale-Dependent Dynamic (LASDD), Wall-Adapting Local Eddy-Viscosity, Turbulent Kinetic Energy, Stability Dependent Smagorinsky, and Anisotropic Minimum-Dissipation (AMD) models. The resolved flow field and turbine loading have shown limited sensitivity to the SGS model with some deviations from the LASDD in wind speed and turbulence intensity at the turbine elevation. This limited sensitivity is owed to the adopted high-resolution grid necessary to provide an acceptable resolution for the actuator-line method. Regarding the computational costs, the LASDD model has the highest compute overhead to the LES compared to the other five SGS models. The AMD model is simple to implement and provides three-dimensional variation of the SGS eddy-viscosity without any parameter tuning, thus it has the highest potential to be used in LES of wind turbines and farms operating in stable conditions.

A semi-empirical model for time-domain tower Vortex induced Vibration load simulations of wind turbines

A new method for simulating aeroelastic resonances between vortex shedding and structural eigenfrequencies of a wind turbine tower is presented in this publication. This aero-elastic effect of Vortex induced Vibrations (ViV) has the potential to disrupt installation processes and cause fatigue and extreme loads on the tower. Despite this issue, there are no established simulation methods available in literature, able and sufficiently efficient to predict the ViV in turbulent and site specific design load conditions. This state-of-the-art is extended by introducing an efficient semi-empirical, time-domain simulation method, which is capable of analyzing the tower ViV excitations and aeroelastic responses in wind turbine load simulations of the isolated tower or the full turbine for fatigue and extreme loads. The method is based on an adaptive harmonic equation, which is automatically tuned to the instantaneous tower motions.

Towards an automated framework for Aero-Servo-Elastic Large Eddy Simulation of wind turbine wakes

During the last two decades, wind turbine wakes have been extensively studied in academia by implementing the Actuator Line method in numerous Large Eddy Simulation solvers tailored for atmospheric flows. However, and while being computationally affordable for ad hoc deep investigations, this approach remains barely used in industry. One of the leading causes is the complexity of the simulation process, which still involves several aspects to be carefully looked at to get valuable results in output. This paper aims to present a workflow that merges and automates the different steps required to conduct aero-servo-elastic Large Eddy Simulations of wind turbines. In particular, a strategy based on an Accurate Conservative Level Set function is used to flag the regions where wakes propagate. This allows to automatically derive refinement zones that cover the wakes at all times. This generic procedure can be seamlessly applied to various farm layouts and inflow conditions. To display the capabilities of the workflow, it is applied to several configurations, including one to seven wind turbines for different inflow conditions. It is observed that lower wind speeds require larger mesh to capture the wake dynamics adequately. Overall, the workflow offers the added advantage of significantly reducing the required human effort while standardizing the process. This is important from an industrial perspective, wherein parametric studies are usually carried out as part of the design process.

Accuracy assessment of Beddoes-Leishman and IAG dynamic stall models for wind turbine applications

The study presents a systematic comparison between two of the most-credited dynamic stall models for wind turbine applications: the original Beddoes-Leishman (BL) model and the newly-developed IAG. The scope of such comparison, supported by experimental data, is to shed new light on the actual suitability of current dynamic stall models for their integration into modern wind turbine simulation codes, and on the best practices to calibrate them. Two different strategies are followed for the calibration of the BL model: 1) standard one, compliant with common practices found in the literature; 2) a physics-oriented one, focusing on the constants defining the dynamic stall onset as well as on the parameters governing the duration of the vortex shedding process. The IAG model, initially developed based on the first-order BL formulation and recently improved by reducing the number of constants and removing compressibility effects, is applied instead in its standard form only. The two models are compared across a range of oscillation mean angles, amplitudes, and reduced frequencies. Results demonstrate that the original BL model, although with a challenging calibration process, when properly tuned, can provide a very good description of aerodynamic unsteady loads. While showing consistent results, the IAG formulation appears to be more robust, as it employs fewer constants and extracts most of the needed information directly from the input polar data. The comparison between the calibrated BL and IAG models highlights critical modelling aspects, the computation of drag and determination of the stall onset above all, offering valuable insights for the future development of dynamic stall formulations.

Validation of a BEM correction model for swept blades using experimental data

This study validates a correction model, which extends standard blade element momentum theory to swept blades and, by doing so, enhances wind turbine simulation predictability for these advanced geometries. This correction model addresses limitations in BEM algorithms, accommodating the complexities of swept blades by considering the sweep-induced tip vortex displacement and curved bound vortex self-induction. The validation is based on previously published results from wind tunnel experiments on a horizontal axis wind turbine with straight and swept blades, providing blade-level aerodynamic data for comprehensive numerical comparisons. In both blade configurations (straight and swept), good agreement is found between experimental and numerical results, validating the numerical approach. For the swept blade case, an additional comparison to a BEM algorithm assuming a straight blade and to one accounting for crossflow is drawn, underscoring the former’s inadequacy for swept blades. Comparably minor differences between the fully-corrected and only crossflow-corrected algorithms render the assessment of the proposed BEM correction model’s added benefit uncertain. Using the validated BEM algorithm, the experimental results are corrected for twist deformations of individual blades, enabling a direct comparison of the campaigns with straight and swept blades. Results align with expectations, indicating sweep-induced reductions in axial induction and blade loads in the swept blade section.

VAST as a generic, modular aeromechanics code for wind turbine simulation

In order to leverage the full potential wind energy, more research is needed both in the field and numerically. At DLR, the need for simulation competencies is expected to be met by the in-house developed generic and highly flexible multi-physics code VAST. While initially aimed at low- to medium-fidelity simulations of helicopter aeromechanics, the code is applicable to other problems like wind turbine computations. The goal of this paper is to present the general concept of VAST and briefly introduce the available physics models. Next to examples of successful application to helicopter simulation problems, first results in the field of wind energy are shown. The well-known IEA 15 MW reference wind turbine is used as a basis to compare VAST — both with a BEMT and a vortex theory inflow model — to other tools with similar and higher-fidelity physics modeling. For the rigid turbine, blade loads are compared with results of other tools using engineering models as well as CFD, showing good overall agreement. A more detailed evaluation of aerodynamic quantities like the angle of attack and the induced velocity field is presented for VAST and the CFD results. An outlook on the ongoing VAST developments is given.

The Underwater Berlin Research Turbine: A Wind Turbine Model for Wake Investigations in a Water Towing Tank

The design of a three-bladed horizontal axis research wind turbine for wake investigations is described. The turbine has a rotor diameter of 1.3 m and will be operated in a large water towing tank at a submergence depth of 2.5 m, yielding 3.3 % blockage. The test rig is configured to allow for underwater-stereo-particle-image-velocimetry measurements of the near and the far wake at chordwise Reynolds numbers approaching 700 000. The low-Reynolds number airfoil SG6040 is selected to constitute the rotor blades. Cavitation-free operation is assured by assigning a rated angle of attack of 1°. The blades are designed to maintain a constant circulation along the blade span and to minimize tip deflections. The blade pitch angles are adjustable. Various blade designs, with and without passive flow control devices, can be tested by replacing individual blade sections. This eliminates the need for multiple sets of blades. Sensors for acquiring the turbine’s thrust, torque, rotational speed, the azimuthal positions of the blades, and the imposed blade root bending moments are incorporated into the design. The wind turbine simulation suite QBlade is utilized to simulate the turbine characteristics. A model of the entire test rig is derived, representing its structural properties. Results from the analytical verification of the structural model are provided. QBlade is utilized to analyze the test rig design by imposing design loads and calculating the modal properties.

Combined Individual Pitch and Flap Control for Load Reduction of Wind Turbines

In this paper individual pitch control is combined with trailing-edge flap (TEF) control, both designed as multi-loop proportional-integral-derivative (PID) controllers, to significantly reduce blade damage equivalent loads. OpenFAST NREL 5MW aerodynamics are enhanced with dedicated aerodynamic polars of TEF blade elements. The NREL 5MW model, including the TEF extension, is incorporated into Simulink, and PID controller parameters are optimized in a closed-loop optimization setup. The DEL decrease is confirmed via an extensive simulation campaign using the non-linear wind turbine simulation environment.