High-fidelity wind farm simulation methodology with experimental validation

Hsieh, Alan S.; Brown, Kenneth A.; deVelder, Nathaniel B.; Herges, Thomas G.; Knaus, Robert C.; Sakievich, Philip J.; Cheung, Lawrence C.; Houchens, Brent C.; Blaylock, Myra L.; Maniaci, David C.

doi:10.1016/j.jweia.2021.104754

Title: High-fidelity wind farm simulation methodology with experimental validation

Journal Article · Mon Sep 06 00:00:00 EDT 2021 · Journal of Wind Engineering and Industrial Aerodynamics

DOI:https://doi.org/10.1016/j.jweia.2021.104754· OSTI ID:1827603

^[1];

^[1]; Herges, Thomas G. ^[1]; Knaus, Robert C. ^[1]; Sakievich, Philip J. ^[1];

^[2];

^[2]; Blaylock, Myra L. ^[2]; Maniaci, David C. ^[1]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sandia National Lab. (SNL-CA), Livermore, CA (United States)

The complexity and associated uncertainties involved with atmospheric-turbine-wake interactions produce challenges for accurate wind farm predictions of generator power and other important quantities of interest (QoIs), even with state-of-the-art high-fidelity atmospheric and turbine models. A comprehensive computational study was undertaken with consideration of simulation methodology, parameter selection, and mesh refinement on atmospheric, turbine, and wake QoIs to identify capability gaps in the validation process. For neutral atmospheric boundary layer conditions, the massively parallel large eddy simulation (LES) code Nalu-Wind was used to produce high-fidelity computations for experimental validation using high-quality meteorological, turbine, and wake measurement data collected at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at Texas Tech University’s National Wind Institute. The wake analysis showed the simulated lidar model implemented in Nalu-Wind was successful at capturing wake profile trends observed in the experimental lidar data.

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Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office

Grant/Contract Number:: NA0003525

OSTI ID:: 1827603

Alternate ID(s):: OSTI ID: 1862460

Report Number(s):: SAND-2021-11014J; 700215

Journal Information:: Journal of Wind Engineering and Industrial Aerodynamics, Vol. 218; ISSN 0167-6105

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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