A new wind-farm parameterization for large-scale atmospheric models

Abkar, Mahdi; Porté‐Agel, Fernando

doi:10.1063/1.4907600

Cited by 82 publications

(99 citation statements)

References 34 publications

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“…Although these parametrisations are not meant to estimate the local velocity field within the wind farm, differences in velocity reduction within the wind farm could affect the velocity in the wake of it. Future implementations may account for the local flow within the wind farm by using data from high-resolution models, which can be input to the mesoscale model via a look-up table as suggested by Badger et al (2013) and Abkar and Porté-Agel (2015). However, we currently have no measurement data in the wind farm wake to validate these approaches for different wind farm layouts.…”

Section: Discussionmentioning

confidence: 99%

“…The major challenge in the parametrisation is to account for the unresolved relevant processes in agreement with the flow equations of the model. In recent years, steady progress has been made in the parametrisation of the effect of wind farms in global and mesoscale models: from the representation of wind farms by an increased roughness length in Keith et al (2004) and Frandsen et al (2009), up to the more advanced drag approaches in Adams and Keith (2007), Blahak et al (2010), Baidya Roy (2011), Jacobson and Archer (2012), Fitch et al (2012), Fitch et al (2013b), and Abkar and Porté-Agel (2015). Apart from a local drag force, an additional turbulence kinetic energy (TKE) source term is assumed in the schemes proposed by Adams and Keith (2007), Blahak et al (2010), Fitch et al (2012), and Abkar and Porté-Agel (2015).…”

Section: Introductionmentioning

confidence: 99%

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The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF

et al. 2015

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Abstract. We describe the theoretical basis, implementation, and validation of a new parametrisation that accounts for the effect of large offshore wind farms on the atmosphere and can be used in mesoscale and large-scale atmospheric models. This new parametrisation, referred to as the Explicit Wake Parametrisation (EWP), uses classical wake theory to describe the unresolved wake expansion. The EWP scheme is validated for a neutral atmospheric boundary layer against filtered in situ measurements from two meteorological masts situated a few kilometres away from the Danish offshore wind farm Horns Rev I. The simulated velocity deficit in the wake of the wind farm compares well to that observed in the measurements, and the velocity profile is qualitatively similar to that simulated with large eddy simulation models and from wind tunnel studies. At the same time, the validation process highlights the challenges in verifying such models with real observations.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF

et al. 2015

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“…The revised model by Emeis (2010) accounts for the spatially averaged momentum-extraction coefficient by turbines, and the parameters become atmosphericstability dependent. However, these models omit the consid-eration of turbine-scale interactions between the hub and the surface (Abkar and Porté-Agel, 2015a;Fitch et al, 2012Fitch et al, , 2013b.…”

Section: Introductionmentioning

confidence: 99%

“…This ratio depends on various factors such as the wind-farm density and layout, and requires preliminary simulation results (Abkar and Porté-Agel, 2015a). Therefore, the publicly available WFP in the WRF model is chosen in this project for observed power comparison.…”

Section: Introductionmentioning

confidence: 99%

“…An approach similar to the WRF WFP proposed by Abkar and Porté-Agel (2015a) relies on an extra parameter, which is the ratio of the free-stream velocity to the horizontally averaged hub-height velocity of a turbine-containing grid cell. This ratio depends on various factors such as the wind-farm density and layout, and requires preliminary simulation results (Abkar and Porté-Agel, 2015a).…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Lee

Lundquist

2017

Geosci. Model Dev.

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Abstract. Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of windturbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

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Simulating effects of a wind‐turbine array using LES and RANS

Vanderwende

Kosović

Lundquist

et al. 2016

J Adv Model Earth Syst

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Growth in wind power production has motivated investigation of wind‐farm impacts on in situ flow fields and downstream interactions with agriculture and other wind farms. These impacts can be simulated with both large‐eddy simulations (LES) and mesoscale wind‐farm parameterizations (WFP). The Weather Research and Forecasting (WRF) model offers both approaches. We used the validated generalized actuator disk (GAD) parameterization in WRF‐LES to assess WFP performance. A 12‐turbine array was simulated using the GAD model and the WFP in WRF. We examined the performance of each scheme in both convective and stable conditions. The GAD model and WFP produced qualitatively similar wind speed deficits and turbulent kinetic energy (TKE) production across the array in both stability regimes, though the magnitudes of velocity deficits and TKE production levels were underestimated and overestimated, respectively. While wake growth slowed in the latter half of the WFP array as expected, wakes did not approach steady state by the end of the array as simulated by the GAD model. A sensitivity test involving the deactivation of explicit TKE production by the WFP resulted in turbulence levels within the array well that were below those produced by the GAD in both stable and unstable conditions. Finally, the WFP overestimated downwind power production deficits in stable conditions because of the lack of wake stabilization in the latter half of the array.

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A new wind-farm parameterization for large-scale atmospheric models

Cited by 82 publications

References 34 publications

The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF

The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Simulating effects of a wind‐turbine array using LES and RANS

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