Title: Investigating wind turbine impacts on near-wake flow using profiling lidar data and large-eddy simulations with an actuator disk model

Abstract

In this study, wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of these changes to atmospheric stability. Significant velocity deficits (VD) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, σ_u, likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σ_u , while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 mmore » resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake VD characteristics, albeit with smaller magnitudes than observed, while σu values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.« less

Authors:

Mirocha, Jeffrey D. ^[1]; Rajewski, Daniel A. ^[2]; Marjanovic, Nikola ^[3]; Lundquist, Julie K. ^[4]; Kosović, Branko  ^[5];

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• Search DOE PAGES for ORCID "0000-0002-1746-0746"

Draxl, Caroline ^[6]; Churchfield, Matthew J. ^[6]

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+ Show Author Affiliations

1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2. Iowa State Univ., Ames, IA (United States)
3. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Univ. of California, Berkeley, CA (United States)
4. Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
5. National Center for Atmospheric Research, Boulder, CO (United States)
6. National Renewable Energy Lab. (NREL), Golden, CO (United States)

Publication Date:

Thu Aug 27 00:00:00 EDT 2015

Research Org.:

Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); NREL (National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Org.:

USDOE National Nuclear Security Administration (NNSA); USDOE Office of Energy Efficiency and Renewable Energy (EERE); National Science Foundation (NSF)

OSTI Identifier:

1814084

Alternate Identifier(s):

OSTI ID: 1225031

Report Number(s):

LLNL-JRNL-663261; NREL/JA-5000-65157
Journal ID: ISSN 1941-7012; 784842; TRN: US2213882

Grant/Contract Number:  

AC52-07NA27344; 1101284; AC36-08GO28308

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Renewable and Sustainable Energy

Additional Journal Information:

Journal Volume: 7; Journal Issue: 4; Journal ID: ISSN 1941-7012

Publisher:

American Institute of Physics (AIP)

Country of Publication:

United States

Language:

English

Subject:

17 WIND ENERGY; 42 ENGINEERING; LIDAR; wind turbines; automatic speech recognition systems; large eddy simulations; computer modeling