Modelling and measurements of wakes in large wind farms

Barthelmie, R.J.; Rathmann, Ole; Frandsen, Sten Tronæs; Hansen, Kurt Schaldemose; Politis, E. S.; Prospathopoulos, John; Rados, K.; Cabezón, D.; Schlez, W.; Phillips, J.; Neubert, Anja; Schepers, J.G.; Pijl, S.P. van der

doi:10.1088/1742-6596/75/1/012049

Cited by 113 publications

(94 citation statements)

References 6 publications

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“…Subsequently we discuss how the CWBL model can be applied to more general configurations and arbitrary wind inflow directions. In sections 3 and 4 the CWBL model results are compared with field measurement data for Horns Rev and Nysted [46,47], see figure 2, and LES results for Horns Rev [2]. The general conclusions are presented in section 5.…”

Section: Introductionmentioning

confidence: 98%

Generalized coupled wake boundary layer model: applications and comparisons with field and LES data for two wind farms

2016

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(2015)) focused on aligned or staggered wind-farms. The generalized CWBL approach combines an analytical Jensen wake model with a "top-down" boundary layer model coupled through an iterative determination of the wake expansion coefficient and an effective wake coverage area for which the velocity at hub-height obtained using both models converges in the "deep-array" portion (fully developed region) of the wind-farm. The approach accounts for the effect of the wind direction by enforcing the coupling for each wind direction.Here we present detailed comparisons of model predictions with LES results and field measurements for the Horns Rev and Nysted wind-farms operating over a wide range of wind inflow directions. Our results demonstrate that two-way coupling between the Jensen wake model and a "top-down" model enables the generalized CWBL model to predict the "deep-array" performance of a wind-farm better than the Jensen wake model alone. The results also show that the new generalization allows us to study a much larger class of wind-farms than the original CWBL model, which increases the utility of the approach for wind-farm designers. Copyright c 2016 John Wiley & Sons, Ltd. KEYWORDSJensen model, wake model, "top-down" model, coupled wake boundary layer (CWBL) model, power production, Horns Rev, Nysted, wind-farm Correspondence r.j.a.m.stevens@utwente.nl Received . . .

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Section: Introductionmentioning

confidence: 98%

Generalized coupled wake boundary layer model: applications and comparisons with field and LES data for two wind farms

2016

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“…It is now well understood that when several wind turbines are clustered together forming a wind farm, the net harvested power is less than what theoretically would be extracted by an equal number of isolated turbines (Barthelmie et al 2010). Several works have analyzed the effects of wind-turbine arrangement and wake superposition on the resultant harvested power (Barthelmie et al 2007(Barthelmie et al , 2009; Barthelemie and Jensen 2010;Porté-Agel et al 2013;Stevens et al 2014) as well as wake interactions and the wake-recovery processes (Frandsen 1992;Emeis and Frandsen 1993;Frandsen et al 2006;Cal et al 2010;Markfort et al 2012). Analytical wake models for wind farms developed decades ago (Lissaman 1979;Jensen 1983;Katic et al 1986) continue to serve as the bedrock of various engineering software packages used for wind-farm design such as the Wind Atlas Analysis and Application Program (WAsP).…”

Section: Introductionmentioning

confidence: 99%

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

Sharma

Parlange

Calaf

2016

Boundary-Layer Meteorol

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The effect of extensive terrestrial wind farms on the spatio-temporal structure of the diurnally-evolving atmospheric boundary layer is explored. High-resolution largeeddy simulations of a realistic diurnal cycle with an embedded wind farm are performed. Simulations are forced by a constant geostrophic velocity with time-varying surface boundary conditions derived from a selected period of the CASES-99 field campaign. Through analysis of the bulk statistics of the flow as a function of height and time, it is shown that extensive wind farms shift the inertial oscillations and the associated nocturnal low-level jet vertically upwards by approximately 200 m; cause a three times stronger stratification between the surface and the rotor-disk region, and as a consequence, delay the formation and growth of the convective boundary layer (CBL) by approximately 2 h. These perturbations are shown to have a direct impact on the potential power output of an extensive wind farm with the displacement of the low-level jet causing lower power output during the night as compared to the day. The low-power regime at night is shown to persist for almost 2 h beyond the morning transition due to the reduced growth of the CBL. It is shown that the wind farm induces a deeper entrainment region with greater entrainment fluxes. Finally, it is found that the diurnally-averaged effective roughness length for wind farms is much lower than the reference value computed theoretically for neutral conditions.

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“…For field data, data have to be filtered for the naturally arising levels of stability. A recent extensive collection of field data, as well as assessment of wake prediction methods, are to be found in the UpWind project (Barthelmie et al, 2011). That study shows, for example, that the airflow at the Horns Rev wind farm during the one year of the data collection was in neutral or near-neutral conditions for only 30% of the time, 25% in stable and 45% in unstable or very unstable conditions.…”

Section: Introductionmentioning

confidence: 99%

Wind-Tunnel Simulation of the Wake of a Large Wind Turbine in a Stable Boundary Layer. Part 1: The Boundary-Layer Simulation

Hancock

Pascheke

2013

Boundary-Layer Meteorol

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Abstract:Measurements have been made in both a neutral and a stable boundary layer as part of an investigation of the wakes of wind turbines in an offshore environment, in the EnFlo stratified flow wind tunnel. The working section is long enough for the flow to have become very nearly invariant with streamwise distance. In order to be systematic, the flow profile generators of Irwintype spires and surface roughness were the same for both neutral and stable conditions. Achieving the required profiles by adjusting the flow generators, even for neutral flow, is a highly iterative art, and the present results indicate that it will be no less iterative for a stable flow (as well as there being more conditions to meet), so this was not attempted in the present investigation. The stablecase flow conformed in most respects to Monin-Obukhov similarity in the surface layer. A linear temperature profile was applied at the working section inlet, resulting in a near-linear profile in the developed flow above the boundary layer and 'strong' imposed stability, while the condition at the surface was 'weak'. Aerodynamic roughness length (mean velocity) was not affected by stability even though the roughness Reynolds number < 1, while the thermal roughness length was much smaller, as is to be expected. The neutral case was Reynolds-number independent, and by inference, the stable case was also Reynolds-number independent.

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Modelling and measurements of wakes in large wind farms

Cited by 113 publications

References 6 publications

Generalized coupled wake boundary layer model: applications and comparisons with field and LES data for two wind farms

Generalized coupled wake boundary layer model: applications and comparisons with field and LES data for two wind farms

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

Wind-Tunnel Simulation of the Wake of a Large Wind Turbine in a Stable Boundary Layer. Part 1: The Boundary-Layer Simulation

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