Development of a Wind Plant Large-Eddy Simulation with Measurement-Driven Atmospheric Inflow: Preprint

Eliot Quon, Matthew Churchfield, Lawrence Cheung, Stefan Kern

Research output: Contribution to conferencePaper

Abstract

This paper details the development of an aeroelastic wind plant model with large-eddy simulation (LES). The chosen LES solver is the Simulator for Wind Farm Applications (SOWFA) based on the OpenFOAM framework, coupled to NREL's comprehensive aeroelastic analysis tool, FAST. An atmospheric boundary layer (ABL) precursor simulation was constructed based on assessments of meteorological tower, lidar, and radar data over a 3-hour window. This precursor was tuned to the specific atmospheric conditions that occurred both prior to and during the measurement campaign, enabling capture of a night-to-day transition in the turbulent ABL. In the absence of height-varying temperature measurements, spatially averaged radar data were sufficient to characterize the atmospheric stability of the wind plant in terms of the shear profile, and near-ground temperature sensors provided a reasonable estimate of the ground heating rate describing the morning transition. A full aeroelastic simulation was then performed for a subset of turbines within the wind plant, driven by the precursor. Analysis of two turbines within the array, one directly waked by the other, demonstrated good agreement with measured time-averaged loads.
Original languageAmerican English
Number of pages17
StatePublished - 2017
EventAmerican Institute of Aeronautics and Astronautics SciTech 2017 - Grapevine, Texas
Duration: 9 Jan 201713 Jan 2017

Conference

ConferenceAmerican Institute of Aeronautics and Astronautics SciTech 2017
CityGrapevine, Texas
Period9/01/1713/01/17

NREL Publication Number

  • NREL/CP-5000-67521

Keywords

  • aeroelastic analyis
  • atmospheric boundary layer
  • FAST
  • large eddy simulation
  • OpenFOAM
  • SOWFA

Fingerprint

Dive into the research topics of 'Development of a Wind Plant Large-Eddy Simulation with Measurement-Driven Atmospheric Inflow: Preprint'. Together they form a unique fingerprint.

Cite this