High-fidelity aeroelastic analyses of wind turbines in complex terrain: FSI and aerodynamic modelling

Abstract. This paper shows high-fidelity Fluid Structure Interaction (FSI) studies applied on the research wind turbine of the WINSENT project. In this project, two research wind turbines are going to be erected in the South of Germany in the WindForS complex terrain test field. The FSI is obtained by coupling the CFD URANS/DES code FLOWer and the multiphysics FEM solver Kratos, in which both beam and shell structural elements can be chosen to model the turbine. The two codes are coupled in both an explicit and an implicit way. The different modelling approaches strongly differ with respect to computational resources and therefore the advantages of their higher accuracy must be correlated with the respective additional computational costs. The presented FSI coupling method has been applied firstly to a single blade model of the turbine under standard uniform inflow conditions. It could be concluded that for such a small turbine, in uniform conditions a beam model is sufficient to correctly build the blade deformations. Afterwards, the aerodynamic complexity has been increased considering the full turbine with turbulent inflow conditions generated from real field data, in both a flat and complex terrains. It is shown that in these cases a higher structural fidelity is necessary. The effects of aeroelasticity are then shown on the phase-averaged blade loads, showing that using the same inflow turbulence, a flat terrain is mostly influenced by the shear, while the complex terrain is mostly affected by low velocity structures generated by the forest. Finally, the impact of aeroelasticity and turbulence on the Damage Equivalent Loading (DEL) is discussed, showing that flexibility is reducing the DEL in case of turbulent inflow, acting as a damper breaking larger cycles into smaller ones.

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AI Assisted High Fidelity Multi-Physics Digital Twin of Industrial Gas Turbines

10.1115/gt2021-58925 ◽

2021 ◽

Author(s):

Senthil Krishnababu ◽

Omar Valero ◽

Roger Wells

Keyword(s):

Gas Turbine ◽

Data Storage ◽

Gas Turbines ◽

Building Blocks ◽

Data Driven ◽

High Fidelity ◽

Test Field ◽

Operating Characteristics ◽

Digital Twin ◽

The Impact

Abstract Data driven technologies are revolutionising the engineering sector by providing new ways of performing day to day tasks through the life cycle of a product as it progresses through manufacture, to build, qualification test, field operation and maintenance. Significant increase in data transfer speeds combined with cost effective data storage, and ever-increasing computational power provide the building blocks that enable companies to adopt data driven technologies such as data analytics, IOT and machine learning. Improved business operational efficiency and more responsive customer support provide the incentives for business investment. Digital twins, that leverages these technologies in their various forms to converge physics and data driven models, are therefore being widely adopted. A high-fidelity multi-physics digital twin, HFDT, that digitally replicates a gas turbine as it is built based on part and build data using advanced component and assembly models is introduced. The HFDT, among other benefits enables data driven assessments to be carried out during manufacture and assembly for each turbine allowing these processes to be optimised and the impact of variability or process change to be readily evaluated. On delivery of the turbine and its associated HFDT to the service support team the HFDT supports the evaluation of in-service performance deteriorations, the impact of field interventions and repair and the changes in operating characteristics resulting from overhaul and turbine upgrade. Thus, creating a cradle to grave physics and data driven twin of the gas turbine asset. In this paper, one branch of HFDT using a power turbine module is firstly presented. This involves simultaneous modelling of gas path and solid using high fidelity CFD and FEA which converts the cold geometry to hot running conditions to assess the impact of various manufacturing and build variabilities. It is shown this process can be executed within reasonable time frames enabling creation of HFDT for each turbine during manufacture and assembly and for this to be transferred to the service team for deployment during field operations. Following this, it is shown how data driven technologies are used in conjunction with the HFDT to improve predictions of engine performance from early build information. The example shown, shows how a higher degree of confidence is achieved through the development of an artificial neural network of the compressor tip gap feature and its effect on overall compressor efficiency.

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Effect of Flow Inclination on Wind Turbine Performance

Journal of Engineering for Gas Turbines and Power ◽

10.1115/1.4007323 ◽

2012 ◽

Vol 134 (12) ◽

Cited By ~ 10

Author(s):

Christina Tsalicoglou ◽

Sarah Barber ◽

Ndaona Chokani ◽

Reza S. Abhari

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Complex Terrain ◽

Wake Flow ◽

Test Facility ◽

Power Coefficient ◽

Incoming Flow ◽

Turbine Performance ◽

The Impact ◽

Blade Element

This work examines the effect of flow inclination on the performance of a stand-alone wind turbine and of wind turbines operating in the wakes of upstream turbines. The experimental portion of this work, which includes performance and flowfield measurements, is conducted in the ETH dynamically-scaled wind turbine test facility, with a wind turbine model that can be inclined relative to the incoming flow. The performance of the wind turbine is measured with an in-line torquemeter, and a 5-hole steady-state probe is used to detail the inflow and wake flow of the turbine. Measurements show that over a range of tip-speed ratios of 4–7.5, the power coefficient of a wind turbine with an incoming flow of 15 deg inclination decreases on average by 7% relative to the power coefficient of a wind turbine with a noninclined incoming flow. Flowfield measurements show that the wake of a turbine with an inclined incoming flow is deflected; the deflection angle is approximately 6 deg for an incoming flow with 15 deg inclination. The measured wake profiles are used as inflow profiles for a blade element momentum code in order to quantify the impact of flow inclination on the performance of downstream wind turbines. In comparison to the case without inclination in the incoming flow, the combined power output of two aligned turbines with incoming inclined flow decreases by 1%, showing that flow inclination in complex terrain does not significantly reduce the energy production.

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Effects From Complex Terrain on Wind-Turbine Performance

Journal of Energy Resources Technology ◽

10.1115/1.4036048 ◽

2017 ◽

Vol 139 (5) ◽

Cited By ~ 15

Author(s):

Ann Hyvärinen ◽

Antonio Segalini

Keyword(s):

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Wind Turbine ◽

Complex Terrain ◽

Positive Impact ◽

Interaction Effects ◽

Turbine Performance ◽

Turbulent Inflow ◽

Wake Interaction ◽

Inflow Conditions

In this work, experimental measurements are made to study wind turbines over complex terrains and in presence of the atmospheric boundary layer. Thrust and power coefficients for single and multiple turbines are measured when introducing sinusoidal hills and spires inducing an artificial atmospheric boundary layer. Additionally, wake interaction effects are studied, and inflow velocity profiles are characterized using hot-wire anemometry. The results indicate that the introduced hills have a positive impact on the wind-turbine performance and that wake-interaction effects are significantly reduced during turbulent inflow conditions.

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Parametric Analysis Using CFD to Study the Impact of Geometric and Numerical Modeling on the Performance of a Small Scale Horizontal Axis Wind Turbine

Energies ◽

10.3390/en15020505 ◽

2022 ◽

Vol 15 (2) ◽

pp. 505

Author(s):

Muhammad Salman Siddiqui ◽

Muhammad Hamza Khalid ◽

Abdul Waheed Badar ◽

Muhammed Saeed ◽

Taimoor Asim

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Reference Frames ◽

Horizontal Axis ◽

Small Scale ◽

High Fidelity ◽

Horizontal Axis Wind Turbine ◽

Rapid Variability ◽

The Impact ◽

Numerical Complexity

The reliance on Computational Fluid Dynamics (CFD) simulations has drastically increased over time to evaluate the aerodynamic performance of small-scale wind turbines. With the rapid variability in customer demand, industrial requirements, economic constraints, and time limitations associated with the design and development of small-scale wind turbines, the trade-off between computational resources and the simulation’s numerical accuracy may vary significantly. In the context of wind turbine design and analysis, high fidelity simulation under full geometric and numerical complexity is more accurate but pose significant demands from a computational standpoint. There is a need to understand and quantify performance deterioration of high fidelity simulations under reduced geometric or numerical approximation on a single small scale turbine model. In the present work, the flow past a small-scale Horizontal Axis Wind Turbine (HAWT) was simulated under various geometric and numerical configurations. The geometric complexity was varied based on stationary and rotating turbine conditions. In the stationary case, simple 2D airfoil, 2.5D blade, 3D blade sections are evaluated, while rotational effects are introduced for the configuration 3D blade, rotor only, and the full-scale wind turbine with and without the inclusion of a nacelle and tower. In terms of numerical complexity, the Single Reference Frame (SRF), Multiple Reference Frames (MRF), and the Sliding Meshing Interface (SMI) is analyzed over Tip Speed Ratios (TSR) of 3, 6, 10. The quantification of aerodynamic coefficients of the blade (Cl, Cd) and turbine (Cp, Ct) was conducted along with the discussion on wake patterns in comparison with experimental data.

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IDDES simulation of the performance and wake dynamics of the wind turbines under different turbulent inflow conditions

Energy ◽

10.1016/j.energy.2021.121772 ◽

2021 ◽

pp. 121772

Author(s):

Guang Chen ◽

Xiao-Bai Li ◽

Xi-Feng Liang

Keyword(s):

Wind Turbines ◽

Turbulent Inflow ◽

Inflow Conditions

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Blind test comparison of the performance and wake flow between two in-line wind turbines exposed to different turbulent inflow conditions

Wind Energy Science ◽

10.5194/wes-2-55-2017 ◽

2017 ◽

Vol 2 (1) ◽

pp. 55-76 ◽

Cited By ~ 33

Author(s):

Jan Bartl ◽

Lars Sætran

Keyword(s):

Wind Tunnel ◽

Wind Turbines ◽

Turbulence Intensity ◽

Wake Flow ◽

Turbulent Shear ◽

Mean Velocity ◽

Blind Test ◽

Turbulent Inflow ◽

The Mean ◽

Inflow Conditions

Abstract. This is a summary of the results of the fourth blind test workshop that was held in Trondheim in October 2015. Herein, computational predictions on the performance of two in-line model wind turbines as well as the mean and turbulent wake flow are compared to experimental data measured at the wind tunnel of the Norwegian University of Science and Technology (NTNU). A detailed description of the model geometry, the wind tunnel boundary conditions and the test case specifications was published before the workshop. Expert groups within computational fluid dynamics (CFD) were invited to submit predictions on wind turbine performance and wake flow without knowing the experimental results at the outset. The focus of this blind test comparison is to examine the model turbines' performance and wake development with nine rotor diameters downstream at three different turbulent inflow conditions. Aside from a spatially uniform inflow field of very low-turbulence intensity (TI = 0.23 %) and high-turbulence intensity (TI = 10.0 %), the turbines are exposed to a grid-generated highly turbulent shear flow (TI = 10.1 %).Five different research groups contributed their predictions using a variety of simulation models, ranging from fully resolved Reynolds-averaged Navier–Stokes (RANS) models to large eddy simulations (LESs). For the three inlet conditions, the power and the thrust force of the upstream turbine is predicted fairly well by most models, while the predictions of the downstream turbine's performance show a significantly higher scatter. Comparing the mean velocity profiles in the wake, most models approximate the mean velocity deficit level sufficiently well. However, larger variations between the models for higher downstream positions are observed. Prediction of the turbulence kinetic energy in the wake is observed to be very challenging. Both the LES model and the IDDES (improved delayed detached eddy simulation) model, however, consistently manage to provide fairly accurate predictions of the wake turbulence.

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Numerical simulations of a large offshore wind turbine exposed to turbulent inflow conditions

Wind Engineering ◽

10.1177/0309524x18756958 ◽

2018 ◽

Vol 42 (2) ◽

pp. 88-96 ◽

Cited By ~ 9

Author(s):

Galih Bangga ◽

Giorgia Guma ◽

Thorsten Lutz ◽

Ewald Krämer

Keyword(s):

Wind Turbine ◽

Three Dimensional ◽

Offshore Wind ◽

Offshore Wind Turbine ◽

Turbulent Inflow ◽

Background Turbulence ◽

High Turbulence ◽

Dynamics Simulations ◽

The Impact ◽

Inflow Conditions

This work is intended to investigate the aerodynamic responses of a large generic 10-MW offshore wind turbine under turbulent inflow conditions. The nonlinear lifting line free vortex wake simulations approach is employed for this purpose, computed using the QBlade code. In these studies, the effects of a three-dimensional correction model for the airfoil polars were studied in advance. For this purpose, the blade element momentum computations employing the corrected polars are performed and compared to computational fluid dynamics simulations, and a good agreement is obtained between both employed approaches. Background turbulence is then imposed in the QLLT simulations with the turbulence intensities ranging from low to high turbulence levels (3%–15%). Furthermore, the impact of wind shear from different locations (offshore and onshore) is investigated in this work.

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Definition and Interpretation of Wind Farm Efficiency in Complex Terrain: A Discussion

Journal of Energy Resources Technology ◽

10.1115/1.4042447 ◽

2019 ◽

Vol 141 (5) ◽

Cited By ~ 3

Author(s):

Davide Astolfi ◽

Francesco Castellani ◽

Ludovico Terzi

Keyword(s):

Wind Turbines ◽

Complex Terrain ◽

Wind Farm ◽

Wind Farms ◽

Offshore Wind ◽

Test Case ◽

Wind Flow ◽

Farm Efficiency ◽

Definition Of ◽

The Impact

The exploitation of wind turbines in complex terrain has recently been growing. The comprehension of wind flow, especially in the downstream area, is by itself a challenging task in complex terrain: even more so, it is difficult to account for the mixing between terrain effects and the wake interactions between nearby turbines. Efficiency is one of the simplest and meaningful metrics for quantifying the impact of wakes on wind farm production, but its definition is well established basically only for offshore wind farms. In this work, the definition of wind farm efficiency is, therefore, discussed, based on the critical points arising in complex terrain, where there can be at the same time a considerable variation of free wind flow along the layout and a directional distortion of the wakes, induced by the terrain. In this work, operational data of a test case wind farm sited in a very complex terrain, featuring 17 multimegawatt wind turbines, are elaborated and inspire a discussion and a novel definition of efficiency, that restores in the complex terrain case the meaning of the efficiency.

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