CFD modelling approaches against single wind turbine wake measurements using RANS

Stergiannis, Nikolaos; Lacor, Christian; Beeck, Jeroen van; Donnelly, R. P.

doi:10.1088/1742-6596/753/3/032062

Cited by 21 publications

(10 citation statements)

References 12 publications

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“…They concluded that the classic AD model is underestimating the velocity deficit, while the fully resolved model agrees well with measurements. The study in the present report is similar to the study done by Stergiannis et al (2016), however, the actuator disk model is improved and the fully resolved model is using a arbitrary mesh interface instead of a moving reference frame. The biggest difference between these two options is that MFR is a steady-state approximation of the transient rotational motion, while the method using AMI is fully transient (simScale Documentation, 2017).…”

Section: Previously Made Wind Turbine Modelsmentioning

confidence: 76%

“…The fully resolved model stood out in accuracy of the wake predictions. Stergiannis et al (2016) compared an traditional actuator disk model to a fully resolved wind turbine with good results, however, they only included the hub and not the nacelle which was mentioned in their suggestions for further work. The difficulties associated with advanced CFD models are revealed and discussed in the work by Tande (2011).…”

Section: Previously Made Wind Turbine Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Wind Turbine Simulations with OpenFOAM

Hoem

2019

Springer Proceedings in Physics

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This report is written in such detail that others may follow it to do the same implementation of an actuator disk model with hub, and create a fully resolved wind turbine model using AMI like I have done, hopefully without all the struggle. I would like to extend my gratitude to those who have helped me on my way to produce my master thesis. First and foremost I would like to thank my supervisor at NTNU Reidar Kristoffersen for all the constructive discussions, motivational talks and helpful input. I would also like to thank the contributors at the CFD-online OpenFOAM forum that has helped me understand and edit code when I have been absolutely stuck. In particular Louis Gagnon: http://louisgagnon.com.

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Section: Previously Made Wind Turbine Modelsmentioning

confidence: 76%

Section: Previously Made Wind Turbine Modelsmentioning

confidence: 99%

Wind Turbine Simulations with OpenFOAM

Hoem

2019

Springer Proceedings in Physics

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“…The --SST turbulence model proposed by Menter [16] was employed to model turbulence. The --SST was extensively utilized in the simulation of wind turbine aerodynamics with results being in good agreement with experiments [14,15].…”

Section: Methodsmentioning

confidence: 98%

“…The mass and momentum conservation equations for incompressible viscous flow were solved using finite volume method. The utilized flow-field analysis software OpenFOAM was validated on the benchmark NREL 5-MW baseline wind turbine by Zhao et al [14,15]. The --SST turbulence model proposed by Menter [16] was employed to model turbulence.…”

Section: Methodsmentioning

confidence: 99%

Bladelets-Winglets on Blades of Wind Turbines: A Multiobjective Design Optimization Study

Reddy

Dulikravich

Sobieczky

2017

Volume 7: Fluids Engineering

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The work presented in this paper used rigorous 3D flow-field analysis combined with multi-objective constrained shape design optimization for the design of bladelet (winglet) configurations for a three-blade propeller type wind turbine. The fluid flow analysis in this work was performed using 3D, steady, incompressible, turbulent flow Reynolds-averaged Navier-Stokes equations in the rotating frame of reference for each combination of a given wind turbine blade and a varying bladelet geometry. The free stream uniform wind speed in all cases was assumed to be 9 m s−1 and rotational speed was 12 rpm. These were off-design conditions for this rotor. The three simultaneous design optimization objectives were: a) maximize the coefficient of power, b) minimize the coefficient of thrust, and c) minimize twisting moment around the blade axis. The bladelet geometry was fully defined by using a small number of parameters. The optimization was carried out by creating a multi-dimensional response surface for each of the simultaneous objectives. The response surfaces were based on radial basis functions, where the support points were designs analyzed using the high fidelity CFD analysis of the full blade + bladelet geometry. The response surfaces were then coupled to a multi-objective optimization algorithm. The predicted values of the objective functions for the optimum designs were then again validated using the high fidelity computational fluid dynamics analysis code. Results for a Pareto optimized bladelet on a given blade indicate that more than 4% increase in the coefficient of power at minimal thrust force penalty is possible compared to the same wind turbine rotor blade without a bladelet.

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“…Due to the complexity of turbulence, it is unlikely that any single RANS turbulence model is fully capable of representing all turbulent flows. However, it has proven to be an accurate means of determining the average forces on a large scale body (Stergiannis et al, 2016). Owing to the high computational cost of DNS, LES and DES, this study implements RANS turbulence modelling.…”

Section: Cfd Model Developmentmentioning

confidence: 99%