Wind Turbine Simulator Research Articles

Characterization of energy transfer and triadic interactions of coherent structures in turbulent wakes

Turbulent wakes are often characterized by dominant coherent structures over disparate scales. Dynamics of their behaviour can be attributed to interscale energy dynamics and triadic interactions. We develop a methodology to quantify the dynamics of kinetic energy of specific scales. Coherent motions are characterized by the triple decomposition and used to define mean, coherent and random velocity. Specific scales of coherent structures are identified through dynamic mode decomposition, whereby the total coherent velocity is separated into a set of velocities classified by frequency. The coherent kinetic energy of a specific scale is defined by a frequency triad of scale-specific velocities. Equations for the balance of scale-specific coherent kinetic energy are derived to interpret interscale dynamics. The methodology is demonstrated on three wake flows: (i) ${Re}=175$ flow over a cylinder; (ii) a direct numerical simulation of ${Re}=3900$ flow over a cylinder; and (iii) a large-eddy simulation of a utility-scale wind turbine. The cylinder wake cases show that energy transfer starts with vortex shedding and redistributes energy through resonance of higher harmonics. The scale-specific coherent kinetic energy balance quantifies the distribution of transport and transfer among coherent, mean and random scales. The coherent kinetic energy in the rotor scales and the hub vortex scale in the wind turbine interact to produce new scales. The analysis reveals that vortices at the blade root interact with the hub vortex formed behind the nacelle, which has implications for the proliferation of scales in the downwind near wake.

Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm

Abstract. With the increasing growth of wind farm installations, the impact of wake effects caused by wind turbines on power output, structural loads, and revenue has become more relevant than ever. Consequently, there is a need for precise simulation tools to facilitate efficient and cost-effective design and operation of wind farms. To address this need, we present HAWC2Farm, a dynamic and versatile aeroelastic wind farm simulation methodology that combines state-of-the-art engineering models to accurately capture the complex physical phenomena in wind farms. HAWC2Farm employs the aeroelastic wind turbine simulator, HAWC2, to model each individual turbine within the wind farm. It utilises a shared, large-scale turbulence box to represent atmospheric flow field effects at the farm level. The methodology incorporates a modified version of the dynamic wake meandering model to accurately capture wake interactions. This approach not only ensures computational efficiency but also provides valuable insights for wind farm design and operation. To assess its performance, HAWC2Farm is compared using time series extracted from field measurements at the Lillgrund wind farm, encompassing various scenarios involving wake steering via yaw control and a turbine shutdown. The results indicate that HAWC2Farm effectively addresses the challenges associated with modelling the complex dynamics within wind farms, thereby enabling more precise, informed, and cost-effective design and operation strategies.

Advanced wind turbine control development using field test analysis for generator overspeed mitigation

AbstractTurbulent and gusty wind conditions can cause generator overspeed peaks to exceed a threshold that then lead to wind turbine shutdowns, which then decrease the energy production of the wind turbines. We derive so‐called “gust measures” that predict when generator overspeed peaks may occur. These gust measures are then used to develop advanced controllers to mitigate generator overspeed peaks so that wind turbines can operate more robustly in difficult wind conditions without exceeding generator overspeed thresholds that would lead to turbine shutdown events. The advanced controllers are demonstrated in nonlinear aeroelastic simulations using the open‐source wind turbine simulation tool OpenFAST. To increase the realism of the simulations, they are run using field‐replicated wind conditions and a wind turbine model based on data from an experimental field campaign on a downscaled demonstrator of a novel extreme‐scale, two‐bladed, downwind rotor design.

Research on the method of digital twin operation and maintenance platform for intelligent early warning of wind turbine tower

Wind power generators have a complex structure and operate in harsh environments, where working conditions are highly variable. As a result, the operation and maintenance of wind turbines face numerous challenges. In response to the need for the development of wind power operation and maintenance informatization, it is necessary to satisfy the requirements for multi-party collaborative monitoring to ensure the long-term safe and reliable operation of wind turbines. In this paper,we proposed a method for building an intelligent early-warning digital twin platform focused on the simulation of wind turbines and tower components. The platform construction method proposed in this article is based on the Web and from the perspective of intelligent operation and maintenance of wind turbines. It establishes a warning model for tower agent simulation and vibration signal time series prediction. The tower mechanism model is established based on the operating data set of a 4MW wind turbine at Shanghai Electric. Different physical responses of the tower under different wind speeds are simulated, and an agent model using LSTM and decision tree models is established for predictive analysis. To account for uncertainty, a Bayesian-LSTM model is established to warn against predictive errors. Finally, a data-driven digital twin wind turbine platform is achieved on the Web.

Fast Frequency Control Strategy for Direct Drive Wind Turbines Considering the Suppression of Secondary Frequency Drop in the Power Grid

Inertia and damping in the power system are important parameters in frequency regulation and oscillation suppression. Inertia will reduce the rate and amplitude of frequency changes after active power sudden changes. Damping in the system can effectively suppress low-frequency oscillations after grid disturbances. As the penetration rate of wind turbines increases, it will significantly reduce the effective inertia in the power grid and reduce the friendliness of wind power grid connection. To provide better frequency support for the power grid in the event of large disturbances in the power system, this paper proposes a fast frequency control strategy for wind farms that considers the suppression of secondary frequency dips in the power grid. The strategy combines frequency droop control with grid frequency bias control and evaluates the kinetic energy reserve online based on wind power prediction and hourly speed, thus balancing the frequency regulation and suppression of secondary frequency dips in the power grid. A 2.5 MW direct drive wind turbine simulation model was built based on the PSCAD simulation platform, verifying the effectiveness of the proposed comprehensive control strategy.

Variable Blade Inertia in State-of-the-Art Wind Turbine Structural-Dynamics Models

This paper presents a comparison of two methods to represent variable blade inertia in two codes for aero-servo-elastic simulations of wind turbines: the nonlinear aeroelastic multi-body model HAWC2 and the nonlinear geometrically exact beam model BeamDyn for OpenFAST. The main goal is to enable these tools to simulate the dynamic behavior of a wind turbine with variable blade inertia. However, current state-of-the-art load simulation tools for wind turbines cannot simulate variable blade inertia, so the source code of these tools must be modified. The validity of the modified codes is proven based on a simple beam model. The validation shows very good agreement between the modified codes of HAWC2, BeamDyn and an analytical calculation. The add-on of variable blade inertias is applied to reduce the mechanical loads of a 5-megawatt reference wind turbine with an integrated hydraulic-pneumatic flywheel in its rotor blades.

On the design and power output response of hydraulic wind turbines

Standard horizontal axis wind turbines typically use gearboxes for large-scale applications and direct coupling for small-scale designs to connect the rotor to the generator. However, gearboxes pose challenges due to their weight, cost, and exposure to dynamic loads and vibrations within the nacelle. A promising alternative is replacing mechanical transmission with a hydrostatic counterpart, offering advantages such as reduced nacelle mass, generator placement at the tower base, and elimination of the gearbox. It can potentially lead to cost savings of up to 20% in the levelized cost of electricity for offshore wind turbines. This study compares regulated hydrostatic transmission with unregulated transmission and damping components under different wind conditions, including atmospheric boundary layer and low-level jet inputs. Dynamic simulations of a horizontal axis wind turbine incorporating a hydrostatic transmission are conducted to evaluate its response to wind fluctuations caused by prevailing wind velocity profiles, atmospheric boundary layer, and low-level jet velocity profiles. Addressing torque fluctuations and power impact on power quality and mechanical components is crucial in wind turbine operation. The proposed hydrostatic transmission includes primary and secondary proportional controllers for adaptability to varying wind speeds, along with integrated accumulators in the high and low-pressure lines. The main findings indicate that the regulated hydrostatic transmission achieves an efficiency range of 69%–75% across various wind velocity profiles, surpassing the unregulated counterpart. It reduces torque fluctuation amplitude by 35% and improves efficiency by nearly 20% compared to the basic transmission. Torque and power fluctuations are also reduced by 35% and 40%. These improvements are attributed to the damping capabilities of the hydrostatic transmission and the actions of the proportional controller. Implementing the regulated hydrostatic transmission offers several technical and economic advantages, including relocating the generator to ground level and achieving continuous hydraulic variable transmissions without the need for a gearbox. The methodology is applicable to a range of wind turbine sizes.

Development of a wind turbine model and simulation platform using an acausal approach: Multiphysics modeling, validation, and control

AbstractThis article presents the development of the Control‐oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS). CRAFTS has a modular, hierarchical model architecture that enables rapid and accurate simulation of wind turbines. The architecture facilitates the incorporation of model variants, and its system reconfiguration features help simulate multiple design variants. CRAFTS also supports the integration of models developed on a causality‐free platform (e.g., Modelica®) with existing causal models. This article focuses on the validation of a land‐based wind turbine models against OpenFAST, an industry‐standard platform, for several test cases. Closed‐loop scenarios are also tested using the standard ROSCO controller and compared against OpenFAST. In addition, a nonlinear controller developed in our prior work is also evaluated. The test cases demonstrate the user‐friendly and computationally efficient capabilities of CRAFTS to facilitate control co‐design, assist in incorporating multiphysics models, be adaptable to design variants, and allow for rapid simulations to validate models and evaluate controllers.

A new coupling of a GPU‐resident large‐eddy simulation code with a multiphysics wind turbine simulation tool

AbstractThe development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large‐eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross‐verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large‐scale meteorological models as boundary conditions.

Numerical Simulations of the NREL Phase VI Wind Turbine with Low-Amplitude Sinusoidal Pitch

Currently, most wind turbine performance analyses and simulations are performed assuming constant pitch and yaw angles during each rotation. Nevertheless, induced vibration or rotor imbalance can affect the pitch or yaw angle within each rotation. In this study, the effects of low-amplitude sinusoidal pitch angle oscillations of the blade on the performance of a wind turbine was investigated numerically by comparing it against the baseline (without pitch variations). Large eddy simulations were performed in which the motion of blades was handled by the curvilinear immersed boundary (CURVIB) method. The grid resolution was increased near the moving immersed boundaries using dynamic overset grids to resolve rotating blades. It was found that low-amplitude (up to 3 degrees) sinusoidal oscillations in the pitch angle negligibly affected the mean torque but increased its fluctuations and created distinct features in the wake of the turbine. In fact, the turbine’s mean torque at wind speed of 15 m/s decreases from 1245 N.m to 1223 N.m, while its fluctuation (standard deviation) increases from 2.85 N.m to 7.94 N.m, with a dynamic pitch of 0.5 degrees and frequency of 3.6 Hz.

Hybrid physical and data driven modeling for dynamic operation characteristic simulation of wind turbine

Accurate simulation of wind turbines is the key to achieve efficient control of wind turbines and optimal scheduling of wind power systems. Most of the existing methods are physical simulation models, which have heavy computational burden, especially for large-scale wind turbines, and the simulation accuracy is poor under complex dynamic operating conditions. In response, this paper proposes a hybrid physical and data driven model for dynamic operation characteristic simulation of wind turbines. Firstly, a database of dynamic characteristics of wind turbine operation under various wind conditions is constructed, and then the sequence learning (Seq2Seq) model is used to mine the time series characteristics of wind turbine operation parameters. Combining with long short-term memory (LSTM) network, the mapping relationship between various operating parameter time series to establish. On this basis, an attention mechanism is added to the model to learn the dynamic response characteristics of rotor inertia to natural wind process. Through numerical example analysis, the method proposed in this paper can accurately excavate and learn the time sequence dynamic characteristics of wind turbine operating conditions and parameters under various wind conditions, thereby improving the simulation accuracy and calculation efficiency of wind turbine output power and load dynamic characteristics. Taking the actual wind turbine operation data as an example, the simulation accuracy of wind turbine output power reaches 99.8%. Compared with traditional methods, and the simulation accuracy of tower root load reaches 88.5%.

Wind Tunnel Experimental Study on the Efficiency of Vertical-Axis Wind Turbines via Analysis of Blade Pitch Angle Influence

This paper presents results of experimental investigations and numerical simulations of a vertical-axis H-type wind turbine, considering the influence of propeller blade pitch angle on turbine characteristics. An innovative airfoil profile based on a modified symmetric NACA0015 airfoil profile was used as the designed blade profile, which was tested in a wind tunnel over a range of Reynolds numbers from 50,000 to 300,000. The phenomenon of angle-of-attack variation and the resulting forces acting on the blades, particularly in the horizontal configuration and vertical axis of rotation, were discussed. Series of experiments were conducted on a 1:1 scale four-bladed turbine model in the wind tunnel to determine the characteristics, specifically the power coefficient distribution over the tip speed ratio for various Reynolds numbers and blade pitch angles. Subsequently, the turbine was modeled using Qblade software, and a series of calculations were performed under the same conditions. The numerical results were validated with the experimental data.

Maximum power point tracking control of wind turbines based on equivalent sinusoidal wind

The optimal parameter model method for maximum power point tracking (MPPT) control of wind turbines has good wind energy capture performance. However, there is a precondition that the quantitative relationship between optimal control parameters and turbulence characteristics is accurately described. The resolution of the existing turbulence frequency characterization indicators are insufficient. Therefore, a large number of sample data need to be obtained to clearly show the statistical relationship between them and the optimal control parameters, which is extremely time-consuming, and has a negative impact on the optimization results of control parameters. This paper equates the turbulent wind to the sinusoidal wind with the objective of the results of both acting on wind turbines are the same, so as to realize the extraction and index description of the dominant turbulent frequency components strongly related to the optimal control parameters. On this basis, a MPPT control method based on equivalent sinusoidal wind is proposed. This method greatly reduces the required sample size, and makes the setting of control parameters closer to the optimal value, which can further improve the efficiency of wind energy capture. Simulation analysis and experimental results based on wind turbine simulator verify the effectiveness of the proposed method.

3D numerical simulation of the Darrieus vertical axis wind turbine with J-type and straight blades under various operating conditions including self-starting mode

A comprehensive three-dimensional numerical analysis is applied in this study to evaluate the competence of the J-type blades in the vertical axis wind turbines under wide range of operating conditions including various wind speeds, tip speed ratios and wind turbulence intensities. It is found that the vortices which are encapsulated in the concave part of the J-type blades escape from the tips of the blades and become stronger than those originated from the straight blades. Such strong wakes behind the J-type blades are responsible for larger negative effects on generating the torque at high tip speed ratios. Neither of the wind speed, nor the wind turbulence intensity have significant effects on performance of the J-type blade turbines. Of particular interest is to discover the behavior of the J-type blade under self-starting conditions which is a major shortcoming with Darrieus turbines. The results show that replacing the straight blades with the J-type blades causes the generated torque to increase by 26.9% and 37.6% at the wind speeds of 10 m/s and 5 m/s, respectively. Better performance of the J-type blades under self-starting conditions, makes them a promising candidate, especially at low wind speed regions such as urban areas.

Data-driven torque and pitch control of wind turbines via reinforcement learning

This paper addresses the torque and pitch control problems of wind turbines. The main contribution of this work is the development of an innovative reinforcement learning (RL)-based control method targeting wind turbine applications. Our RL-based control framework synergistically combines the advantages of deep neural networks (DNNs) and model predictive control (MPC) technologies. The proposed control strategy is data-driven, adapting to real-time changes in system dynamics and enhancing control performance and robustness. Additionally, the incorporation of an MPC structure within our design improves learning efficiency and reduces the high computational complexity typically found in deep RL algorithms. Specifically, a DNN is designed to approximate the wind turbine dynamics based on a continuously updated dataset composed of state and action measurements taken at specified sampling intervals. The real-time control policy is generated by integrating the online trained DNN into an MPC architecture. The proposed method iteratively updates the DNN and control policy in real-time to optimize performance. As a primary result of this work, the proposed method demonstrates superior robustness and control performance compared to commonly-employed MPC and other baseline wind turbine controllers in the presence of uncertainties and unexpected actuator faults. This effectiveness is showcased through simulations with a high-fidelity wind turbine simulator.

Numerical investigation and aerodynamic simulation of Darrieus H-rotor wind turbine at low Reynolds numbers

ABSTRACT In order to select an airfoil suitable for the wind tunnel testing on a three-bladed Darrieus H-rotor wind turbine, several symmetrical National Advisory Committee for Aeronautics (NACA) 4-digit, NACA 4-digit, NACA 5-digit, and Selig airfoils with chord Reynolds numbers ( R e c ) of 17,890, 35,780, and 53,670 were studied. To achieve higher aerodynamic performance at Re of 17,890 to 53,670, the NACA0015 airfoil was selected. The lift coefficient ( R e c ) of the NACA0015 airfoil after shape modification has reached values of 0.788 to 0.936 at Re of 35,780 and 0.925 to 1.027 at Re of 53,670 with the same stall angle ( A o A s t a l l ) in both investigated Re, according to the results of modifying the airfoil’s thickness and chord. Additionally, the NACA0015 modified airfoil’s maximum lift-to-drag ratio coefficient ( C L / C D ) increased by 34.01% and 17.94% at Re of 35780 and 53,670, respectively. Likewise, the analysis showed that the NACA0015 modified airfoil’s maximum performance coefficient ( C P ) increased from 0.129, 0.242, 0.285, 0.308, and 0.33 to 0.152, 0.272, 0.307, 0.331, and 0.354 at Re of 100,000, 150000, 200000, 250000, and 300,000, respectively. As well as the findings demonstrated that the XFOIL code provides the most accurate overall prediction results at low Re.

Sustainability of the Permanent Magnet Synchronous Generator Wind Turbine Control Strategy in On-Grid Operating Modes

Today, there are a variety of technologies for wind-generating systems, characterized by component complexity and control. Controllers are essential for the sustainability of the output voltage and the optimal speed of the generator. To overcome the problems, the system must use controllers that determine the controllers’ ability relative to each other and ultimately the controller that behaves better. This paper investigates the simulation of a PMSG wind turbine with PI, PID, neutral-point-clamped (NPC) and fuzzy controllers to study performance at different wind speeds as input. The wind energy is converted by the wind turbine and given to the PMSG generator. The PMSG output power is transferred to the power network; in this case, we have modeled the power network with a three-phase load. In order to confirm the performance of the proposed method, a PMSG wind turbine is simulated using MATLAB R2017. The simulation results show that the controllers can adjust the DC link voltage, the active power produced by the wind system.

The large-scale impact of anthropogenic mixing by offshore wind turbine foundations in the shallow North Sea

Structure drag from offshore wind turbines and its physical impacts on the marine environment of the German Bight are investigated in this study. The flow past vertical cylinders, such as wind turbine foundations, and associated turbulent mixing has long been studied, but questions remain about anticipated regional implications of offshore wind infrastructure on physical and biogeochemical conditions. Here, we present two existing modeling approaches for simulating wind turbine foundation effects in regional ocean models and discuss the problematic use of very high resolution in hydrostatic modeling. By implementing a low-resolution structure drag parameterization in an unstructured-grid model, we demonstrate the impacts of monopile drag on hydrodynamic conditions, validated against recent in-situ measurements. Although the anthropogenic mixing is confined at wind farm sites, our simulations show that structure-induced mixing affects much larger, regional scales. The additional turbulence production emerges as the driving mechanism behind the monopile impacts, leading to changes in both the current velocities and stratification, with magnitudes of about 10%, similar in magnitude to regional annual and interannual variabilities. This study provides new insights into the hydrodynamic impact of offshore wind farms at their current development levels and emphasizes the need for further research in view of potential restructuring of the future coastal environment.

Quantifying and clustering the wake-induced perturbations within a wind farm for load analysis

The main objective of the HIPERWIND project is to reduce the Levelized Cost Of Energy by controlling the uncertainties in a chain of numerical models simulating an offshore wind farm. This paper studies the wake-induced perturbations of the ambient wind conditions inside a wind farm. A theoretical floating offshore wind farm off the coast of South Brittany in France is considered as a test case, and a numerical model simulating the wake of this farm is exploited. This model gives an analytical prediction of wake deficit and added turbulence, also considering the influence of the floaters’ position due to mean wind forces. An uncertainty propagation on the wake model is performed, considering the multivariate joint distribution of ambient wind conditions as input. This results, for each turbine, in a wake-modified probabilistic distribution on the wind speed and turbulence intensity averaged over the rotor. A new approach for clustering these wake-modified distributions is proposed in this paper to regroup the wind turbines exposed to similar environmental conditions, leading to a similar structural response. This analysis is essential to ensure the practical feasibility of the reliability analysis of an overall project with the computational cost of aero-servo-hydro-elastic simulations of offshore wind turbines. Several methods classically used for clustering are compared. Finally, four clusters only are sufficient to represent the whole set of turbines in the wind farm.

Multi-scale modeling of a wind turbine wake in complex terrain

Comparing numerical simulations of wind turbine wakes in neutral atmospheric boundary layer (ABL) flow over complex terrains with full-scale experiments is not always straightforward. Pure neutral ABL conditions are rarely found in the atmosphere as the characteristics of the ABL change during the diurnal cycle. This study presents some insights into how a single wind turbine (WT) and its wake behave under near-neutral ABL conditions in complex terrain. The Perdigão Valley in Portugal was chosen as the test case as it is an excellent case study of three-dimensional flow in complex terrain to validate numerical simulations of WT wake with experimental data due to the availability of extensively deployed remote sensing equipment (e.g., German Aerospace Center (DLR) and Technical University of Denmark (DTU) multi-Doppler lidars). The Weather Research and Forecasting (WRF) [1] model is utilized in large-eddy simulation (LES) mode in order to simulate the period of interest with a multi-scale modeling approach. Five nested domains, with the finest domain having a spatial resolution of 5 m, are used to dynamically downscale mesoscale flow features to microscale. A generalized actuator line (GAL) WT parameterization is used to model the wind turbine-flow interaction. WRF-LES-GAL (hereinafter referred to as WLG) results compare quite well with the experimental data obtained from lidars and meteorological mast, with minor biases between the simulated and observed data. Due to insufficient buoyancy generation from the WRF-LES model, the simulated track wake was found to have lower vertical deflection compared to the lidar data; hence, no recirculation zone is observed in the valley. Overall, the WLG model is able to reproduce the wake characteristics observed on the first ridge top into the valley, as well as the power and thrust generation, and can be used for further analysis of other stability conditions.