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Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

Journal Article · · Wind Energy Science (Online)
 [1];  [2];  [3];  [4];  [1];  [5];  [6]
  1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
  2. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  3. NSF National Center for Atmospheric Research, Boulder, CO (United States)
  4. Princeton Univ., NJ (United States)
  5. Johns Hopkins Univ., Baltimore, MD (United States); National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  6. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Mesoscale model predictions of wind, turbulence, and wind energy capacity factors are evaluated in the Altamont Pass Wind Resource Area of California (APWRA), where the diurnal regional sea breeze and associated terrain-driven speedup flows drive wind energy production during the summer months. Results from the Weather Research and Forecasting model version 4.4 using a novel three-dimensional planetary boundary layer (3D PBL) scheme, which treats both vertical and horizontal turbulent mixing, are compared to those using a well-established one-dimensional (1D) scheme that treats only vertical turbulent mixing. Each configuration is evaluated over a nearly 3-month-long period during the Hill Flow Study, and due to the recurring nature of the observed speedup flows, diurnal composite averaging is used to capture robust trends in model performance. Both model configurations showed similar overall skill. The general timing and direction of the speedup flows is captured, but their magnitude is overestimated within a typical wind turbine rotor layer. Both also fail to capture a persistent observed near-surface jet-like flow, likely due to the limited grid resolution that is typical of mesoscale models. However, the 3D PBL configuration shows several minor improvements over the 1D PBL configuration, including improved wind speed and turbulence kinetic energy profiles during the accelerating phase of the speedup events, as well as reduced positive wind speed bias at surface stations across the APWRA region. Using a mesoscale wind farm parameterization, modeled capacity factors are also compared to monthly data reported to the US Energy Information Administration (EIA) during the study period. Although the monthly trend in the data is captured, both model configurations overestimate capacity factors by roughly 7 %–11 %. Through model evaluation, this study provides confidence in the 3D PBL scheme for wind energy applications in complex terrain and provides guidance for future testing.
Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); National Renewable Energy Laboratory (NREL), Golden, CO (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
Grant/Contract Number:
AC05-76RL01830; AC36-08GO28308; AC52-07NA27344
OSTI ID:
2584394
Alternate ID(s):
OSTI ID: 2571687
OSTI ID: 3003450
Report Number(s):
LLNL--JRNL-870130; NREL/JA--5000-91491; PNNL-SA--205190
Journal Information:
Wind Energy Science (Online), Journal Name: Wind Energy Science (Online) Journal Issue: 7 Vol. 10; ISSN 2366-7451
Publisher:
Copernicus PublicationsCopyright Statement
Country of Publication:
United States
Language:
English

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