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Hybrid RANS-LES of the Atmospheric Boundary Layer for Wind Farm Simulations

Conference ·
DOI:https://doi.org/10.2514/6.2022-1922· OSTI ID:1845668

Wind farm simulations often do not accurately represent wake-atmospheric boundary layer (ABL) interactions, blade boundary layer (BL) dynamics, and turbine-turbine interactions. In this work, we use Active Model Split (AMS), a new hybrid Reynolds-Averaged Navier Stokes (RANS)-large eddy simulation (LES) model, which is well suited to capture these effects because the model can (i) accurately simulate the ABL with the Coriolis effect, (ii) is accurate in adverse pressure gradients such as those near wind turbine blades, and (iii) has sufficiently low computational cost to simulate multiple turbines while resolving the blade BL. For simplicity and consistency we develop AMS to be used throughout the domain rather than in a zonal method. We implement our work in the massively parallel flow solver, Nalu-Wind, so that our model can access the compute resources needed for blade-resolved simulations of multiple wind turbines. To accomplish these aims, we modify the baseline AMS by changing the RANS contribution to SST k - omega with a length scale limiter, adding the Coriolis effect, and developing an appropriate wall treatment. We show that AMS of the ABL with the Coriolis effect matches LES reference results better than those obtained with RANS. We describe our plans to add buoyancy effects and wind turbines to our AMS simulations.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Computational Science Graduate Fellowship; USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA); USDOE Exascale Computing Project; USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1845668
Report Number(s):
NREL/CP-2C00-80183; MainId:42386; UUID:934068f3-084c-44ac-97df-6d1c3222e874; MainAdminID:61671
Resource Relation:
Conference: Presented at the AIAA SCITECH 2022 Forum, 3-7 January 2022, San Diego, California
Country of Publication:
United States
Language:
English

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