Short-Term Numerical Forecasting of Near-Ground Wind Fields Using OpenFOAM Coupled With WRF

Onel, Huseyin C.; Tuncer, İsmail H.

doi:10.2514/6.2023-1737

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…Given this multi-scale nature, a meso-to-micro numerical downscaling could be useful in simulating the ABL-turbine interaction realistically and understanding its underlying mechanisms (Muñoz-Esparza et al, 2014;Bakhoday-Paskyabi et al, 2022a). To incorporate realistic ABL conditions, one can use the meso-micro offline coupling approach; i.e., the output of a mesoscale model is used as the driven boundary condition for the dedicated LES models (e.g., Wang et al, 2020;Lin et al, 2021;Bakhoday-Paskyabi et al, 2022b;Onel and Tuncer, 2023). However, this approach depends on the frequency of the mesoscale model output, which is often not enough for short-timescale processes.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation

Bui,

Bakhoday-Paskyabi,

Mohammadpour-Penchah

2024

Geosci. Model Dev.

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Abstract. In this study, we present the development of a Simple Actuator Disk model for Large-Eddy Simulation (SADLES), implemented within the Weather Research and Forecasting (WRF) model, which is widely used in atmospheric research. The WRF-SADLES model supports both idealized studies and realistic applications through downscaling from realistic data, with a focus on resolutions of tens of meters. Through comparative analysis with the Parallelized Large-eddy Simulation Model (PALM) at resolutions of 10 and 30 m, we validate the effectiveness of WRF-SADLES in simulating the wake characteristics of a 5 MW wind turbine. Results indicate good agreement between WRF-SADLES at 30 m resolution and 10 m resolution and the PALM model. Additionally, we demonstrate a practical case study of WRF-SADLES by downscaling ERA5 reanalysis data using a nesting method to simulate turbine wakes at the Alpha Ventus wind farm in the south of the North Sea. The meso-to-micro downscaling simulation reveals that the wake effect simulated by WRF-SADLES at the FINO1 offshore meteorological mast station aligns well with the cup anemometer and lidar measurements. Furthermore, we investigate an event of farm-to-farm interaction, observing a 16 % reduction in ambient wind speed and a 38 % decrease in average turbine power at Alpha Ventus due to the presence of a wind farm to the southwest. WRF-SADLES offers a promising balance between computational efficiency and accuracy for wind turbine wake simulations, making it valuable for wind energy assessments and wind farm planning.

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Section: Introductionmentioning

confidence: 99%