Wind Turbine Simulator Research Articles

A novel python-based floating offshore wind turbine simulation framework

The expansion of floating offshore wind brings the industry closer to achieving commercial viability. However, the challenging environment characterised by strong winds, waves, and currents, along with the growing size of wind turbines and the dynamic behaviour of floaters, introduces concerns about power production efficiency and system durability due to increased fatigue loads, which subsequently impacts overall costs. In an attempt to mitigate the financial implications coming from alterations made to control strategies and structural elements during the initial design phase, this paper propounds an all-encompassing simulation framework for offshore wind turbines. The current study thoroughly explores the various capabilities of the tool, with a focus on its simulation models. Importantly, the paper highlights the complex interactions between tool models and different controllers. Carefully designed, this tool offers users a variety of functions to enhance system design, fine-tune control strategies, and thoroughly assess performance metrics. The paper elaborates on these aspects, providing an explanation of the tool's capabilities and enhancing the dynamic comparison between the models.

Numerical simulation and experimental data blade investigation of horizontal wind turbine

The article presents the results of numerical simulation of a wind turbine blade. The fundamental formulas of the theory of aerodynamics, on which the calculations are based, are presented. Computer models of air movement near the blade are shown. Data on the distribution of speed have been obtained. The coefficient of wind energy utilization depends on the parameters of both the oncoming flow and the blade profile. This coefficient is different for vertical and horizontal wind turbines. To improve the operation of the wind turbine, it is proposed to use non-network algorithms. The neural network should collect data on the received errors in the system of mechanization and automatic control. Errors in control systems are analyzed, individual parameters are weighted to stabilize the operation of the wind turbine as a whole.

Numerical simulation of wind turbines conducted using COMSOL software

The article presents the results of modeling air flow in a turbulent mode of flow around a wind device as profiles and fields of pressure and velocity. The simulation was performed with the help of the COMSOL software package. The axial velocity profile, pressure coefficient around the blade and instantaneous power coefficient of one blade using the transient SST model are in good agreement with the experimental data. The presented values of the device’s power factor Cp were obtained using different turbulence models. When mathematically modeling the flow around a vertical axis wind turbine, the transient SST turbulence model can be used, which provides satisfactory results.

Calibration method of the k-ω SST turbulence model for wind turbine performance prediction near stall condition

The present study intends to enhance the accuracy of the k–ω SST turbulence model for numerical wind turbine simulation in stall condition. In order to achieve this purpose a calibration approach is proposed, and is applied to NREL S826 NTNU wind rotor. This method consists in adjusting the two turbulence model coefficients: a1 and β*, which are found to be 0.8 and 0.45 respectively. Then the calculated power and thrust coefficients are compared to the experimental results. The power coefficient results revealed that the simulation relative error at the range of tip speed ratio between 3 to 6 where light stall occurs, is reduced from 17.89 % to 4.58 % by application of calibration. The effects of calibration on flow behaviour are implemented thereafter, by analysing pressure, and skin friction coefficients distribution along the blade. The limiting streamlines on the blade suction side are examined for more flow behaviour understanding. The effects on turbulent kinetic energy around the blade are also highlighted. The main important conclusions that can be made is that calibration reduce the separation zone on the blade suction side, and limits the vortex shedding strength, leading to improve the rotor efficiency and hence to improve the model accuracy.

Optimal airfoil selection for small horizontal axis wind turbine blades: A multi-criteria approach

Over the last century, the growing demand for clean energy has emphasized wind energy as a promising solu-tion to address contemporary energy challenges. Within the realm of wind energy, the wind turbine plays a pivotal role in harnessing the kinetic energy of the wind and converting it into electrical power. Among the various components of the wind turbine system, turbine blades assume a critical role in capturing the wind's kinetic energy and converting it into rotational motion. Consequently, the design of wind turbine blades holds the utmost importance in determining the overall performance and efficiency of the entire wind turbine system. One essential aspect of blade design involves selecting an appropriate airfoil. Throughout history, numerous airfoil profiles have been developed for various applications. Notably, National Advisory Committee for Aeronautics (NACA) and National Renewable Energy Laboratory (NREL) airfoils have been tailored for aircraft and large-scale wind turbine blades, respectively. However, the quest for suitable airfoil types for small-scale wind turbine blades has been ongoing. This study delves into an examination of over 62 distinct NACA and NREL aerofoil types tailored for small horizontal-axis wind turbine blades. Employing specialized software, namely QBlade, specifically designed for modeling and simulating wind turbine blades, the study calculates key parameters such as power output, stress, deformation, and weight for each airfoil. Subsequently, based on the simulated data, the optimal airfoil is identified using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria selection approach. This selection process takes into account simulation results pertaining to power output, stress, deformation, and weight. The decision-making process involving multiple criteria is facilitated using Excel and Python. The findings of this study reveal that among the 62 airfoil types under consideration, the NACA 0024, NACA 2424, and NACA 4424 airfoils emerge as the most suitable choices for small horizontal-axis wind turbine blades.

Numerical Framework for the Coupled Analysis of Floating Offshore Multi-Wind Turbines

Floating offshore multi-wind turbines (FOMWTs) are an interesting alternative to the up-scaling of wind turbines. Since this is a novel concept, there are few numerical tools for its coupled dynamic assessment at the present time. In this work, a numerical framework is implemented for the simulation of multi-rotor systems under environmental excitations. It is capable of analyzing a platform using leaning towers that handle wind turbines with their own features and control systems. This tool is obtained by coupling the seakeeping hydrodynamics solver SeaFEM with the single wind turbine simulation tool OpenFAST. The coupling of SeaFEM provides a higher fidelity hydrodynamic solution, allowing the simulation of any structural design using the finite element method (FEM). Additionally, a methodology is proposed for the extension of the single wind solver, allowing for the analysis of multi-rotor configurations. To do so, the solutions of the wind turbines are computed independently using several OpenFAST instances, performing its dynamic interaction through the floater. This method is applied to the single turbine Hywind concept and the twin-turbine W2Power floating platform, supporting NREL 5-MW wind turbines. The rigid-body response amplitude operators (RAOs) are computed and compared with other numerical tools. The results showed consistency in the developed framework. An agreement was also obtained in simulations with aerodynamic loads. This resulting tool is a complete time-domain aero–hydro–servo–elastic solver that is able to compute the combined response and power generation performance of multi-rotor systems.

Design and realization of a pre-production platform for wind turbine manufacturing

Addressing the challenge of rehearsing large-scale equipment assembly, particularly for oversized components like wind turbine towers, hubs, nacelles, and blades, which often face quality issues such as substandard workmanship and wide tolerances during on-site assembly, a system has been developed for simulating wind turbine assembly. This system enables digital wind turbine assembly by creating virtual and production process models and employing intelligent database analysis. It resolves the problem of the absence of pre-production for large-scale equipment, meets the batch production needs of the wind turbine manufacturing industry, enhances the safety of wind turbine operations, improves operator assembly skills, and boosts production efficiency. This platform has already been implemented in the wind turbine manufacturing industry, yielding significant economic benefits.

A Short Review on the Time-Domain Numerical Simulations for Structural Responses in Horizontal-Axis Offshore Wind Turbines

In addition to a carbon-neutral vision being recognized worldwide, the utilization of wind energies via horizontal-axis wind turbines, especially in offshore areas, has been intensively investigated from an academic perspective. Numerical simulations play a significant role in the design and optimization of offshore wind turbines. The current review focuses on studies concerning the numerical simulations of offshore wind turbine dynamics, including the modelling of the aerodynamic and hydrodynamic conditions of the environment and the reduced-order modelling of the wind turbine dynamic responses. In detail, the functions and mechanisms of each module in the numerical simulation of the wind turbine dynamics are articulated, which in turn demonstrates its importance for the design of offshore wind turbines, and hence the development of the offshore wind industry. Based on this review, it is argued that the vertical variations in wind velocities, the blade element momentum theory, the wave dynamic models, and the reduced-order model for structural dynamics are the major concerns for the numerical simulation of wind turbines. Consequently, such directions should be emphasized in future studies.

Vibration-based rotation speed estimation for Industrial IoT

The Industrial Internet of Things (IIoT) uses wireless vibration sensors to predict machine health. In many cases, communication bandwidth and sensor processing resources are limited, and machine kinematics is not available at the sensor level. Consequently, only basic condition indicators, such as overall signal energy or peak-to-peak values, are computed at the sensor and transmitted to the cloud for further analysis. The behavior of these indicators is strongly influenced by machine speed, which is not available in many cases. This paper presents a novel and straightforward method for estimating machine relative speed based on vibrations, enhancing the interpretation of changes in basic condition indicators. The method does not require any prior knowledge about the machine's kinematics or expected speed changes. It was evaluated on simulated signals and wind turbine vibrations, providing a general solution for estimating varying rotating speed when no supplementary information is available. The method estimates rotating speed up to a constant factor in a set of signals (or signal segments) by optimally utilizing peak frequency statistics in the spectrum. The method demonstrates high accuracy under different operating conditions and noise and holds the potential to be used in a variety of IIoT applications.

A new methodology for upscaling semi-submersible platforms for floating offshore wind turbines

Abstract. This paper presents a new upscaling methodology for semi-submersible floating offshore wind turbine platforms. The size and power rating of offshore wind turbines have been growing in recent years, with modern wind turbines rated at 10–18 MW in contrast with 2–5 MW in 2010. It is not apparent how much further wind turbine size can be increased before it is unjustified. Scaling relations are a useful method for analyzing wind turbine designs to understand the mass, load, and cost increases with size. Scaling relations currently do not exist but are needed for floating offshore platforms to understand how the technical and economic development of floating offshore wind energy may develop with increasing turbine size. In this paper, a hydrodynamic model has been developed to capture the key platform response in pitch. The hydrodynamic model is validated using OpenFAST, a high-fidelity offshore wind turbine simulation software. An upscaling methodology is then applied to two semi-submersible case studies of reference systems (the Offshore Code Comparison Collaboration Continuation (OC4) 5 MW and the International Energy Agency (IEA) 15 MW). For each case study, the platform pitch angle at rated wind turbine thrust is constrained to a specified value. The results show that platform dimensions scale to a factor of 0.75, and the platform steel mass scales to a factor of 1.5 when the wall thickness is kept constant. This study is the first to develop generalized upscaling relations that can be used for other triangular semi-submersible platforms that have three outer columns with the turbine mounted at the center of the system. This is in contrast with other studies that upscale a specific design to a larger power rating. This upscaling methodology provides new insight into trends for semi-submersible platform upscaling as turbine size increases.

Reliability of simplified wind fields and structure models for the response simulation of parked offshore wind turbines

Over the past few decades, offshore wind turbines (OWTs) have been popular in the wind engineering and renewable energy fields. Numerous studies have investigated the dynamic responses of OWTs by numerical simulation. However, the different numerical models gave different results, making it difficult to compare and select models for different design and research purposes. In this study, six models including the main wind field and structure model were built based on the National Renewable Energy Laboratory 5-MW OWT, and the dynamic responses were simulated to compare and quantify the effects of the models on the response of the parked OWT. The results show that a uniform distribution of the wind field is too conservative for estimating the dynamic responses of the parked OWT. The structural response calculated using a uniformly distributed wind field is twice as large as those with the spatial distribution and coherence of the wind speed. The wind profile significantly affected the response of the parked OWT, particularly on the standard deviation of the displacement. When estimating the dynamic response of the tower of a parked OWT, the simplified model, in which the blades and wind load are simplified as a concentrated mass and load, is relatively reliable. The maximum displacement at the tower top of the simplified model is close to that of the detailed model. However, a detailed model is necessary to obtain the blade responses and accurate power spectral density of the structural response. In addition, the wind-field model significantly affected the spectral characteristics of the dynamic response of the blades.

A model reference adaptive control framework for floating offshore wind turbines with collective and individual blade pitch strategy

The utilization of floating offshore wind turbines is regarded as a promising solution for offshore renewables, wherein blade pitch control plays a crucial role in both operation and maintenance. Among the various blade pitch control methods, strategies that involve more states pertaining to the control objectives demonstrate superior tracking performance. However, these approaches necessitate additional linearization and parameter tuning efforts, particularly when addressing varying operating conditions in real-world unsteady environments. In this study, a decoupled model reference adaptive control framework with inner control laws for ideal responses for both collective and individual blade pitch is employed, in the context of floating offshore wind turbine control problems during operation beyond rated conditions. According to the simulations conducted on a benchmark wind turbine simulator under a series of turbulent wind speeds, the proposed integrated controller achieved reductions in power fluctuation and damage equivalent load in blades compared to corresponding baseline controllers, at the expense of acceptable deterioration in tower base loads and blade actuator activities. The proposed scheme demonstrates its adaptability in serving the entire operating range, mitigating the need for parameter tuning due to variations in wind speed, and exhibits potential to involve more control purposes.

Variable cross-sectional effect on bi-directional blades–tower–soil–structure dynamic interaction on offshore wind turbine subject to wind–wave loads

BackgroundThis study introduces a numerical model designed to simulate interactions occurring between a wind turbine's tower and the surrounding soil, as well as between the nacelle, blades, and the surrounding environment. This simulation accounts for both fore–aft and side-to-side movements. To describe these interactions, the model leverages the Euler–Lagrange equations. It calculates wave loads utilizing the Morison equation, with wave data generated based on the JONSWAP spectrum. Furthermore, aerodynamic loads are determined using the blade element moment theory, and the wind spectrum is generated using the Von Karman turbulence model. The tower is represented as a variable cross-sectional beam, employing a two-noded Euler beam element with two degrees of freedom: transverse displacement and rotation, and utilizing Hermite polynomial shape functions.ResultsIn a comparative analysis against experimental data, this modified model demonstrates significant enhancements in accurately reproducing the dynamic behavior of wind turbines with variable cross-sectional towers, outperforming models that approximate the tower with a constant cross section. Our findings reveal that the modified model achieves a remarkable improvement of 15% in replicating the tower's dynamic response when compared to the constant cross-sectional models. As a case study, a 5 MW monopile wind turbine with a flexible foundation, specifically the one provided by the National Renewable Energy Laboratory (NREL), is employed to simulate its dynamic response.ConclusionsThis research presents a robust numerical model for simulating wind turbine behavior in various environmental conditions. The incorporation of variable cross-sectional tower representation significantly improves the model's accuracy, making it a valuable tool for assessing wind turbine dynamics. The study's findings highlight the importance of considering tower flexibility in wind turbine simulations to enhance their real-world applicability.

The impacts of atmospheric icing on performance and behavior of a controlled large-scale wind turbine

Icing degrades turbine performance by altering the geometry of blade airfoils, reducing turbine power output, and increasing structural loads. In this study, the impacts of atmospheric icing on the full performance and behavior of a controlled large-scale wind turbine are thoroughly investigated. Using the Mustafa Sahin bladed wind turbine simulation model, the National Renewable Energy Laboratory 5 MW turbine is simulated with and without iced blades. The turbine blades are considered fully covered by light icing at the leading edge, which causes a reduction of up to 9.27% in Cl and an increase of up to 48% in Cd data of blade airfoils. Turbine static performance and behavior are examined at different uniform winds between cut-in and cut-out wind speeds, while the dynamic performance and behavior are estimated under turbulent winds at below (region II) and above (region III) rated regions. Simulation results are presented in terms of various turbine parameters, such as rotor power, thrust, their coefficients, blade pitch angle, rotor speed, etc. Results show that such light icing alters the turbine's aerodynamic characteristics and dynamics, increasing the turbine's cut-in and rated wind speeds, and reducing the thrust and maximum power coefficients by 5.5% and 13.35%, respectively. Under the same uniform winds, due to icing, turbine static performance and behavior are drastically disrupted in below rated region, resulting in reduced rotor speed, turbine efficiency, thrust, and power output by up to 4.77%, 39.7%, 7.63%, and 40%, respectively. In region III, however, thrust increases by up to 15% although the power output, rotor speed, and turbine efficiency do not change considerably. When the dynamic responses are examined under turbulent wind with a mean of 7.9 m/s in region II, mean power and fluctuations reduce by 14.17% and 10.88%, respectively. The mean thrust decreases by 6.86%, while its fluctuations reduce by 11.33%. The mean rotor speed reduces by 3.83%, and its fluctuations decrease by 12.84%. Under turbulent wind with a mean of 15.7 m/s in region III, the mean power and fluctuations decrease by 0.053% and 1.95%, respectively. The mean thrust increases by 11.99% and its fluctuations drop by 0.84%. The mean rotor speed does not change much, but its fluctuations increase by 0.132%. The mean blade pitch angle reduces by 9.39%, while its fluctuations increase by 7.39%.

Convex economic model predictive control for blade loads mitigation on wind turbines

AbstractEconomic model predictive control (EMPC) has received increasing attention in the wind energy community due to its ability to trade‐off economic objectives with ease. However, for wind turbine applications, inherent nonlinearities, such as from aerodynamics, pose difficulties in attaining a convex optimal control problem (OCP), by which real‐time deployment is not only possible but also a globally optimal solution is guaranteed. A variable transformation can be utilized to obtain a convex OCP, where nominal variables, such as rotational speed, pitch angle, and torque, are exchanged with an alternative set in terms of power and energy. The ensuing convex EMPC (CEMPC) possesses linear dynamics, convex constraints, and concave economic objectives and has been successfully employed to address power control and tower fatigue alleviation. This work focuses on extending the blade loads mitigation aspect of the CEMPC framework by exploiting its individual pitch control (IPC) capabilities, resulting in a novel CEMPC‐IPC technique. This extension is made possible by reformulating static blade and rotor moments in terms of individual blade aerodynamic powers and rotational kinetic energy of the drivetrain. The effectiveness of the proposed method is showcased in a mid‐fidelity wind turbine simulation environment in various wind cases, in which comparisons with a basic CEMPC without load mitigation capability and a baseline IPC are made.

Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers

Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers

Lidar-based virtual load sensors for mooring lines using artificial neural networks

Floating offshore wind turbines are equipped with a variety of sensors, which are measuring data, valuable for the control and monitoring of the turbine. However, reliable measurements are difficult or costly for some physical quantities. This includes load estimates for mooring lines and fairleads. In this study, we investigate an approach using wind speed measurements from a forward-looking nacelle-based lidar as inputs to long short-term memory networks to estimate fairlead tensions. Nacelle-based lidar wind speed measurements on floating offshore wind turbines are influenced by platform motions, in particular by the rotational pitch displacement and the surge displacement of the floater. Therefore, the lidar wind speed measurement contains information about the dynamic behavior of the floater. In turn, the floater’s dynamics determine the fair lead loads. Thus in this study, we directly use the lidar-measured line of sight (LOS) wind speeds to estimate mooring line tensions. The model training data is obtained using the aero-elastic wind turbine simulation tool openFAST in combination with the numerical lidar simulation framework ViConDAR. Results show, that lidar-based virtual load sensors can reproduce mean fairlead tension as well as low-frequency fluctuations, with varying accuracy dependant on the combination of input features. For the model which is only using LOS wind speed measurements as input a normalized root mean squared error of 0.55 was obtained.

Active disturbance rejection control and multi-objective optimization for wind turbine active power regulation

Wind energy is anticipated to become a backbone of the future energy system and provide active power ancillary services. In this paper, a novel active power control (APC) scheme is proposed to deal with the active power regulation problem for the wind turbine. Firstly, an APC strategy dual-activating the pitch action and the rotor kinetic energy is designed to specify the reference signals of pitch angle and rotor speed. Next, a multi-variable controller based on active disturbance rejection control (ADRC) theory is proposed to implement the APC strategy, wherein the theoretical proof of the convergence result is provided. Then, a multi-objective coronavirus herd immunity optimization algorithm is proposed to find out the Pareto solution of controller parameter tuning, in which the power tracking accuracy and fatigue load mitigation are considered. Finally, the performance superiority of the proposed APC strategy is verified on a 5 MW OpenFAST wind turbine simulator in case of the IEC turbulence wind field and the reg-D standard test signal into account. Compared with the conventional pitch angle control and rotor speed control strategies, our APC scheme is able to accomplish the task of power regulation with smaller tracking root mean square error, shorter pitch travel and lighter fatigue load.

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.