Turbulence Optimized Park model with Gaussian wake profile

Pedersen, Jesper Grønnegaard; Svensson, E; Poulsen, Louise K.; Nygaard, Nicolai

doi:10.1088/1742-6596/2265/2/022063

Cited by 15 publications

(28 citation statements)

References 21 publications

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“…The second aim of this study is to compare the wind turbine power output of the LES model PALM with two analytical wake models: The NP model (Niayifar and Porté-Agel, 2016) and the TurbOPark model (Pedersen et al, 2022). The comparison shows that there are large discrepancies between the wind farm power predicted by the wake models and by PALM.…”

Section: Discussionmentioning

confidence: 99%

“…In the next section the wind turbine power output of PALM is discussed and compared with two analytical wake models, which are described in this section shortly. The two wake models are the NP model (Niayifar and Porté-Agel, 2016) and the Turbulence Optimized Park (TurbOPark) model (Pedersen et al, 2022). These wake models are chosen because they have a Gaussian velocity deficit profile in the wake and because their wake expansion rate depends on the local TI.…”

Section: Description Of the Analytical Wake Modelsmentioning

confidence: 99%

“…The aim of this study is to fill this research gap by comparing two analytical wake models with a large-eddy simulation of a 15 GW wind farm. The NP model (Niayifar and Porté-Agel, 2016) and the TurbOPark model (Pedersen et al, 2022) are chosen because they use a Gaussian wake profile and a turbulence model. Potential discrepancies in the power output are identified and explained by an energy budget analysis.…”

Section: Introductionmentioning

confidence: 99%

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Large-eddy simulation of a 15 GW wind farm: Flow effects, energy budgets and comparison with wake models

Maas

2023

Front. Mech. Eng.

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Planned offshore wind farm clusters have a rated capacity of more than 10 GW. The layout optimization and yield estimation of wind farms is often performed with computationally inexpensive, analytical wake models. As recent research results show, the flow physics in large (multi-gigawatt) offshore wind farms are more complex than in small (sub-gigawatt) wind farms. Since analytical wake models are tuned with data of existing, sub-gigawatt wind farms they might not produce accurate results for large wind farm clusters. In this study the results of a large-eddy simulation of a 15 GW wind farm are compared with two analytical wake models to demonstrate potential discrepancies. The TurbOPark model and the Niayifar and Porté-Agel model are chosen because they use a Gaussian wake profile and a turbulence model. The wind farm has a finite size in the crosswise direction, unlike as in many other large-eddy simulation wind farm studies, in which the wind farm is effectively infinitely wide due to the cyclic boundary conditions. The results show that new effects like crosswise divergence and convergence occur in such a finite-size multi-gigawatt wind farm. The comparison with the wake models shows that there are large discrepancies of up to 40% between the predicted wind farm power output of the wake models and the large-eddy simulation. An energy budget analysis is made to explain the discrepancies. It shows that the wake models neglect relevant kinetic energy sources and sinks like the geostrophic forcing, the energy input by pressure gradients and energy dissipation. Taking some of these sources and sinks into account could improve the accuracy of the wake models.

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Section: Discussionmentioning

confidence: 99%

Section: Description Of the Analytical Wake Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Large-eddy simulation of a 15 GW wind farm: Flow effects, energy budgets and comparison with wake models

Maas

2023

Front. Mech. Eng.

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“…While conventional wake models (Jensen 1983; Ainslie 1988; Bastankhah & Porté-Agel 2014; Niayifar & Porté-Agel 2016) look at only the turbine scale, efforts to include some of the large-scale physics have been attempted by Pedersen et al (2022) with the introduction of the so-called turbulence-optimized park model. On the other hand, a new class of models has emerged, adopting a ‘coupled’ approach wherein conventional turbine-scale wake models are coupled suitably with additional sub-models aimed at capturing the meso-scale physics that is otherwise absent.…”

Section: Introductionmentioning

confidence: 99%

A shear stress parametrization for arbitrary wind farms in conventionally neutral boundary layers

Stipa,

Allaerts,

Brinkerhoff

2024

J. Fluid Mech.

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In the context of large off-shore wind farms, power production is influenced greatly by the turbine array's interaction with the atmospheric boundary layer. One of the most influencing manifestations of such complex interaction is the increased level of shear stress observed within the farm. This leads to higher momentum fluxes that affect the wind speed at the turbine locations and in the cluster wake. At the wind farm entrance, an internal boundary layer (IBL) grows due to the change in effective roughness imposed by the wind turbines, and for large enough clusters, this can reach the unperturbed boundary layer height in what is referred to as the fully developed regime. Downwind, a second IBL starts growing, while the shear stress profile decays exponentially to its unperturbed state. In the present study, we propose a simple analytical model for the vertical profile of the horizontal shear stress components in the three regions identified above. The model builds upon the top-down model of Meneveau (J. Turbul., vol. 13, 2012, N7), and assumes that the flow develops in a conventionally neutral boundary layer. The proposed parametrization is verified successfully against large-eddy simulations, demonstrating its ability to capture the vertical profile of horizontal shear stress, and its evolution both inside and downwind of the wind farm. Our findings suggest that the developed model can prove extremely useful to enhance the physical grounds on which new classes of coupled wind farm engineering models are based, leading to a better estimation of meso-scale phenomena affecting the power production of large turbine arrays.

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“…Abkar & Porté-Agel 2015; Xie & Archer 2015; Pedersen et al. 2022; Vahidi & Porté-Agel 2022) or to capture effects of yaw angle (e.g. Bastankhah & Porté-Agel 2016; King et al.…”

Section: Introductionmentioning

confidence: 99%

A fast-running physics-based wake model for a semi-infinite wind farm

Bastankhah,

Mohammadi,

Lees

et al. 2024

J. Fluid Mech.

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This paper presents a new generation of fast-running physics-based models to predict the wake of a semi-infinite wind farm, extending infinitely in the lateral direction but with finite size in the streamwise direction. The assumption of a semi-infinite wind farm enables concurrent solving of the laterally averaged momentum equations in both streamwise and spanwise directions. The developed model captures important physical phenomena such as vertical top-down transport of energy into the farm, variable wake recovery rate due to the farm-generated turbulence and also wake deflection due to turbine yaw misalignment and Coriolis force. Of special note is the model's capability to predict and shed light on the counteracting effect of Coriolis force causing wake deflections in both positive and negative directions. Moreover, the impact of wind farm layout configuration on the flow distribution is modelled through a parameter called the local deficit coefficient. Model predictions were validated against large-eddy simulations extending up to 45 km downstream of wind farms. Detailed analyses were performed to study the impacts of various factors such as incoming turbulence, wind farm size, inter-turbine spacing and wind farm layout on the farm wake.

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Turbulence Optimized Park model with Gaussian wake profile

Cited by 15 publications

References 21 publications

Large-eddy simulation of a 15 GW wind farm: Flow effects, energy budgets and comparison with wake models

Large-eddy simulation of a 15 GW wind farm: Flow effects, energy budgets and comparison with wake models

A shear stress parametrization for arbitrary wind farms in conventionally neutral boundary layers

A fast-running physics-based wake model for a semi-infinite wind farm

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