skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set

Abstract

Offshore wind resource assessments for the conterminous U.S. and Hawai’i have been developed before, but Alaska’s offshore wind resource has never been rigorously assessed. Alaska, with its vast coastline, presents ample potential territory in which to build offshore wind farms, but significant challenges have thus far limited Alaska’s deployment of utility-scale wind energy capacity to a modest 62 MW (or approximately 2.7% of the state’s electric generation) as of this writing, all in land-based wind farms. This study provides an assessment of Alaska’s offshore wind resource, the first such assessment for Alaska, using a 14-year, high-resolution simulation from a numerical weather prediction and regional climate model. This is the longest-known high-resolution model data set to be used in a wind resource assessment. Widespread areas with relatively shallow ocean depth and high long-term average 100-m wind speeds and estimated net capacity factors over 50% were found, including a small area near Alaska’s population centers and the largest transmission grid that, if even partially developed, could provide the bulk of the state’s energy needs. The regional climate simulations were validated against available radiosonde and surface wind observations to provide the confidence of the model-based assessment. The model-simulated wind speed was found tomore » be skillful and with near-zero average bias (-0.4–0.2 m s-1) when averaged over the domain. Small sample sizes made regional validation noisy, however.« less

Authors:
ORCiD logo; ORCiD logo; ; ; ; ORCiD logo
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1543344
Alternate Identifier(s):
OSTI ID: 1545584
Report Number(s):
NREL/JA-5000-71112
Journal ID: ISSN 1996-1073; ENERGA; PII: en12142780
Grant/Contract Number:  
AHA-7-70142-01; AC36-08GO28308
Resource Type:
Published Article
Journal Name:
Energies (Basel)
Additional Journal Information:
Journal Name: Energies (Basel) Journal Volume: 12 Journal Issue: 14; Journal ID: ISSN 1996-1073
Publisher:
MDPI AG
Country of Publication:
Switzerland
Language:
English
Subject:
17 WIND ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; Alaska; offshore wind energy; resource assessment; WRF; regional climate simulation; model wind validation

Citation Formats

Lee, Jared A., Doubrawa, Paula, Xue, Lulin, Newman, Andrew J., Draxl, Caroline, and Scott, George. Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set. Switzerland: N. p., 2019. Web. doi:10.3390/en12142780.
Lee, Jared A., Doubrawa, Paula, Xue, Lulin, Newman, Andrew J., Draxl, Caroline, & Scott, George. Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set. Switzerland. doi:10.3390/en12142780.
Lee, Jared A., Doubrawa, Paula, Xue, Lulin, Newman, Andrew J., Draxl, Caroline, and Scott, George. Fri . "Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set". Switzerland. doi:10.3390/en12142780.
@article{osti_1543344,
title = {Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set},
author = {Lee, Jared A. and Doubrawa, Paula and Xue, Lulin and Newman, Andrew J. and Draxl, Caroline and Scott, George},
abstractNote = {Offshore wind resource assessments for the conterminous U.S. and Hawai’i have been developed before, but Alaska’s offshore wind resource has never been rigorously assessed. Alaska, with its vast coastline, presents ample potential territory in which to build offshore wind farms, but significant challenges have thus far limited Alaska’s deployment of utility-scale wind energy capacity to a modest 62 MW (or approximately 2.7% of the state’s electric generation) as of this writing, all in land-based wind farms. This study provides an assessment of Alaska’s offshore wind resource, the first such assessment for Alaska, using a 14-year, high-resolution simulation from a numerical weather prediction and regional climate model. This is the longest-known high-resolution model data set to be used in a wind resource assessment. Widespread areas with relatively shallow ocean depth and high long-term average 100-m wind speeds and estimated net capacity factors over 50% were found, including a small area near Alaska’s population centers and the largest transmission grid that, if even partially developed, could provide the bulk of the state’s energy needs. The regional climate simulations were validated against available radiosonde and surface wind observations to provide the confidence of the model-based assessment. The model-simulated wind speed was found to be skillful and with near-zero average bias (-0.4–0.2 m s-1) when averaged over the domain. Small sample sizes made regional validation noisy, however.},
doi = {10.3390/en12142780},
journal = {Energies (Basel)},
number = 14,
volume = 12,
place = {Switzerland},
year = {2019},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.3390/en12142780

Save / Share:

Works referenced in this record:

Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations
journal, January 2007


A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes
journal, September 2006

  • Hong, Song-You; Noh, Yign; Dudhia, Jimy
  • Monthly Weather Review, Vol. 134, Issue 9
  • DOI: 10.1175/MWR3199.1

On wind turbine loads during the evening transition period
journal, June 2019

  • Lu, Nan‐You; Basu, Sukanta; Manuel, Lance
  • Wind Energy, Vol. 22, Issue 10
  • DOI: 10.1002/we.2355

Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models
journal, January 2008

  • Iacono, Michael J.; Delamere, Jennifer S.; Mlawer, Eli J.
  • Journal of Geophysical Research, Vol. 113, Issue D13
  • DOI: 10.1029/2008JD009944

Wind resource assessment offshore the Atlantic Iberian coast with the WRF model
journal, February 2018


Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic
journal, April 2014


Wind climate estimation using WRF model output: method and model sensitivities over the sea: Offshore wind climate estimation using WRF output
journal, December 2014

  • Hahmann, Andrea N.; Vincent, Claire L.; Peña, Alfredo
  • International Journal of Climatology, Vol. 35, Issue 12
  • DOI: 10.1002/joc.4217

Wind and solar resource data sets: Wind and solar resource data sets
journal, December 2017

  • Clifton, Andrew; Hodge, Bri-Mathias; Draxl, Caroline
  • Wiley Interdisciplinary Reviews: Energy and Environment, Vol. 7, Issue 2
  • DOI: 10.1002/wene.276

High-Resolution Historical Climate Simulations over Alaska
journal, March 2018

  • Monaghan, Andrew J.; Clark, Martyn P.; Barlage, Michael P.
  • Journal of Applied Meteorology and Climatology, Vol. 57, Issue 3
  • DOI: 10.1175/JAMC-D-17-0161.1

The Wind Integration National Dataset (WIND) Toolkit
journal, August 2015


Using a coupled lake model with WRF for dynamical downscaling: WRF WITH LAKE MODEL FOR DOWNSCALING
journal, June 2014

  • Mallard, Megan S.; Nolte, Christopher G.; Bullock, O. Russell
  • Journal of Geophysical Research: Atmospheres, Vol. 119, Issue 12
  • DOI: 10.1002/2014JD021785

River flow forecasting through conceptual models part I — A discussion of principles
journal, April 1970


A Description of the Advanced Research WRF Version 3
text, January 2008

  • Skamarock, William; Klemp, Joseph; Dudhia, Jimy
  • UCAR/NCAR
  • DOI: 10.5065/D68S4MVH

Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization
journal, December 2008

  • Thompson, Gregory; Field, Paul R.; Rasmussen, Roy M.
  • Monthly Weather Review, Vol. 136, Issue 12
  • DOI: 10.1175/2008MWR2387.1

The parametrization of surface fluxes in large-scale models under free convection
journal, January 1995

  • Beljaars, Anton C. M.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 121, Issue 522
  • DOI: 10.1002/qj.49712152203

The Weather Research and Forecasting Model: Overview, System Efforts, and Future Directions
journal, August 2017

  • Powers, Jordan G.; Klemp, Joseph B.; Skamarock, William C.
  • Bulletin of the American Meteorological Society, Vol. 98, Issue 8
  • DOI: 10.1175/BAMS-D-15-00308.1

A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics
journal, January 2012


The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins
journal, January 2011

  • Yang, Zong-Liang; Niu, Guo-Yue; Mitchell, Kenneth E.
  • Journal of Geophysical Research, Vol. 116, Issue D12
  • DOI: 10.1029/2010JD015140

Offshore wind power simulation by using WRF in the central coast of Chile
journal, August 2016


The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements
journal, January 2011

  • Niu, Guo-Yue; Yang, Zong-Liang; Mitchell, Kenneth E.
  • Journal of Geophysical Research, Vol. 116, Issue D12
  • DOI: 10.1029/2010JD015139

The ERA-Interim reanalysis: configuration and performance of the data assimilation system
journal, April 2011

  • Dee, D. P.; Uppala, S. M.; Simmons, A. J.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 137, Issue 656
  • DOI: 10.1002/qj.828

Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand
journal, November 2017


Offshore wind speed estimates from a high-resolution rapidly updating numerical weather prediction model forecast dataset
journal, December 2017

  • James, Eric P.; Benjamin, Stanley G.; Marquis, Melinda
  • Wind Energy, Vol. 21, Issue 4
  • DOI: 10.1002/we.2161

Turbulence in an atmosphere with a non-uniform temperature
journal, January 1971


Cheyenne: SGI ICE XA Cluster
service, January 2017

  • Laboratory, Computational And Information Systems
  • UCAR/NCAR
  • DOI: 10.5065/D6RX99HX

A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh
journal, April 2016

  • Benjamin, Stanley G.; Weygandt, Stephen S.; Brown, John M.
  • Monthly Weather Review, Vol. 144, Issue 4
  • DOI: 10.1175/MWR-D-15-0242.1

Non-steady wind turbine response to daytime atmospheric turbulence
journal, March 2017

  • Nandi, Tarak N.; Herrig, Andreas; Brasseur, James G.
  • Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 375, Issue 2091
  • DOI: 10.1098/rsta.2016.0103