Comparison of Wake Model Simulations with Offshore Wind Turbine Wake Profiles Measured by Sodar

Barthelmie, R.J.; Larsen, Gitte; Frandsen, Sten Tronæs; Folkerts, L.; Rados, K.; Pryor, Sara C.; Lange, Bernhard; Schepers, Gerard

doi:10.1175/jtech1886.1

Cited by 290 publications

(164 citation statements)

References 12 publications

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“…To assess the agreement on the centreline the coefficient of determination [33] has been calculated for two different actuator turbine models. This approach has previously been used for comparing between wind turbine modelling data and experiments [34]. The coefficient of determination was 0.94 for the RANS + BE model and 0.92 for the RANS + Disk model (where 1 indicates perfect agreement).…”

Section: (B) Wakementioning

confidence: 99%

Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines

Batten

Harrison

Bahaj

2013

Phil. Trans. R. Soc. A.

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The actuator disc-RANS model has widely been used in wind and tidal energy to predict the wake of a horizontal axis turbine. The model is appropriate where large-scale effects of the turbine on a flow are of interest, for example, when considering environmental impacts, or arrays of devices. The accuracy of the model for modelling the wake of tidal stream turbines has not been demonstrated, and flow predictions presented in the literature for similar modelled scenarios vary significantly. This paper compares the results of the actuator disc-RANS model, where the turbine forces have been derived using a blade-element approach, to experimental data measured in the wake of a scaled turbine. It also compares the results with those of a simpler uniform actuator disc model. The comparisons show that the model is accurate and can predict up to 94 per cent of the variation in the experimental velocity data measured on the centreline of the wake, therefore demonstrating that the actuator disc-RANS model is an accurate approach for modelling a turbine wake, and a conservative approach to predict performance and loads. It can therefore be applied to similar scenarios with confidence.

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Section: (B) Wakementioning

confidence: 99%

Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines

Batten

Harrison

Bahaj

2013

Phil. Trans. R. Soc. A.

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“…Wakes behind horizontal axis wind turbines are turbulent flow structures with rotational motion being induced by the turbine blades, radial pressure gradients, tip vortices 3 and complex flows from the tower and the hub (Mo and Lee, 2011;Wagner et al, 1996). From the perspective of a wind farm optimal layout, the grouping of the wind turbines introduces two major issues: (1) A wind turbine operating in the wake of another turbine has a reduced power output because of the velocity deficit introduced by the upstream wind turbine during the process of momentum extraction from wind, and (2) Due to the large increase in the turbulence intensity (TI) in the wake and the consequent increase in the dynamic loads, the lifespan of the wind turbine blade operating in the wake is shortened (Barthelmie et al, 2009;Barthelmie et al, 2006;Chamorro and Porté-Agel, 2009;Sanderse, 2009) and therefore results in increased maintenance costs. Hence the study of wind turbine wakes is of paramount importance in order to increase the power output and operation life of the blades.…”

Section: Introductionmentioning

confidence: 99%

“…A number of attempts have been made to establish more accurate wake models. However, so far advanced and detailed wake models, even when including an explicit representation of turbulence and its impact on the wake expansion, have not been able to produce significantly improved predictions (Barthelmie et al, 2006). Similarly, a number of researchers have used CFD, based on the RANS equations to acquire comparatively fast results (Menter et al, 2006;Potsdam and Mavriplis, 2009;Sørensen et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Effects of wind speed changes on wake instability of a wind turbine in a virtual wind tunnel using large eddy simulation

Choudhry

Arjomandi

et al. 2013

Journal of Wind Engineering and Industrial Aerodynamics

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Large Eddy Simulation (LES) of the NREL (National Renewable Energy Laboratory) Phase VI wind turbine inside a virtual wind tunnel, with the same test section as that of NASA Ames 24.4 m × 36.6 m, was carried out in order to analyse and better understand the wake instability and its breakdown behind the wind turbine. LES was performed using the commercial CFD software, ANSYS FLUENT, based on the dynamic Smagorinsky-Lilly model. The wind turbine was placed at a distance of two rotor diameters from the upstream boundary with a downstream domain of twenty rotor diameters in length The results of the simulation were compared with the experimental data published by the NREL and a good agreement was found between the two. Furthermore, the average turbulence intensities from the LES were compared with a semi-empirical model and very good agreement was observed, except for the regions of on-going wake instability and vortex breakdown. It was observed that the wake behind the wind turbine consists of a system of intense and stable rotating helical vortices.These vortices persisted for some distance downstream of the wind turbine and finally become unstable producing a sinuous shape. The downstream distance at which wake instability and vortex breakdown occur, was observed to be a function of the upstream wind speed. For example, for an upstream wind speed of 7 m/s, it was observed that the primary vortex structure became unstable at a downstream distance of four rotor diameters and complete breakdown occurred at approximately six rotor diameters. On the other hand, when the upstream wind speed was 15.1 m/s, wake instability occurred at approximately eleven rotor diameters downstream of the wind turbine and complete breakdown was observed at thirteen rotor diameters downstream of the wind turbine. Furthermore, it was observed that the turbulence intensity rapidly decreased during the process of wake instability and vortex breakdown; the location of the decrease is a function of the upstream wind speed. It is suggested that the distinction between the near and far wake can be identified as the average location between the start of the wake instability and the end of the process, at complete breakdown. Therefore the average location of this boundary is a function of the upstream wind speed. Hence for upstream wind speeds of 7 m/s, 10 m/s, 13.1 m/s and 15.1 m/s, the boundary between the near and far wake lies at five, seven, ten and twelve rotor diameters downstream respectively.

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“…Our ability to gain such understanding is limited by the lack of experimental techniques able to quantify turbulent flows at the utility turbine scale. Current field measurement techniques provide only point velocity characterization (sonic anemometers) or velocity profiles (LiDAR and Sodar) at a coarse spatio-temporal resolution [7][8][9] . Particle image velocimetery (PIV), based on tracking the displacement of tracers in an illuminated flow field 10,11 , is the only measurement technique capable of obtaining planar velocity distributions with the spatio-temporal resolution required to study flow-structure interactions.…”

mentioning

confidence: 99%

Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine

et al. 2014

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To improve power production and structural reliability of wind turbines, there is a pressing need to understand how turbines interact with the atmospheric boundary layer. However, experimental techniques capable of quantifying or even qualitatively visualizing the large-scale turbulent flow structures around full-scale turbines do not exist today. Here we use snowflakes from a winter snowstorm as flow tracers to obtain velocity fields downwind of a 2.5-MW wind turbine in a sampling area of B36 Â 36 m 2 . The spatial and temporal resolutions of the measurements are sufficiently high to quantify the evolution of bladegenerated coherent motions, such as the tip and trailing sheet vortices, identify their instability mechanisms and correlate them with turbine operation, control and performance. Our experiment provides an unprecedented in situ characterization of flow structures around utility-scale turbines, and yields significant insights into the Reynolds number similarity issues presented in wind energy applications.

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Comparison of Wake Model Simulations with Offshore Wind Turbine Wake Profiles Measured by Sodar

Cited by 290 publications

References 12 publications

Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines

Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines

Effects of wind speed changes on wake instability of a wind turbine in a virtual wind tunnel using large eddy simulation

Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine

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