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

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.

[1]  A. Obukhov,et al.  Turbulence in an atmosphere with a non-uniform temperature , 1971 .

[2]  W. Collins,et al.  Radiative forcing by long‐lived greenhouse gases: Calculations with the AER radiative transfer models , 2008 .

[3]  Lance Manuel,et al.  On wind turbine loads during the evening transition period , 2019, Wind Energy.

[4]  Bri-Mathias Hodge,et al.  Wind and solar resource data sets , 2018 .

[5]  Jeffrey G. Arnold,et al.  Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .

[6]  Yves Gagnon,et al.  Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand , 2017 .

[7]  Martyn P. Clark,et al.  High-Resolution Historical Climate Simulations over Alaska , 2018 .

[8]  Siqhamo Yamkela Ntola Convention on the Law of the Sea and Blue Economy , 2018, The Blue Economy Handbook of the Indian Ocean Region.

[9]  Donna Heimiller,et al.  2016 Offshore Wind Energy Resource Assessment for the United States , 2016 .

[10]  Kevin W. Manning,et al.  The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins , 2011 .

[11]  J. Dudhia,et al.  A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes , 2006 .

[12]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[13]  Vahan Gevorgian,et al.  A Spatial-Economic Cost-Reduction Pathway Analysis for U.S. Offshore Wind Energy Development from 2015–2030 , 2016 .

[14]  G. Grell,et al.  A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh , 2016 .

[15]  Stanley G. Benjamin,et al.  Offshore wind speed estimates from a high‐resolution rapidly updating numerical weather prediction model forecast dataset , 2018 .

[16]  C. Guedes Soares,et al.  Resource Assessment Methods in the Offshore Wind Energy Sector , 2016 .

[17]  Cristian Mattar,et al.  Offshore wind power simulation by using WRF in the central coast of Chile , 2016 .

[18]  Da‐Lin Zhang,et al.  A High-Resolution Model of the Planetary Boundary Layer—Sensitivity Tests and Comparisons with SESAME-79 Data , 1982 .

[19]  Jordan G. Powers,et al.  The Weather Research and Forecasting Model: Overview, System Efforts, and Future Directions , 2017 .

[20]  C. Vincent,et al.  Wind climate estimation using WRF model output: method and model sensitivities over the sea , 2015 .

[21]  G. Powers,et al.  A Description of the Advanced Research WRF Version 3 , 2008 .

[22]  C. Draxl,et al.  Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes , 2014 .

[23]  Kevin W. Manning,et al.  The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements , 2011 .

[24]  Tanya L. Spero,et al.  Using a coupled lake model with WRF for dynamical downscaling , 2014 .

[25]  Wei Huang,et al.  NCAR Command Language (NCL) , 2012 .

[26]  A. Monin,et al.  Basic laws of turbulent mixing in the surface layer of the atmosphere , 2009 .

[27]  A. Beljaars The parametrization of surface fluxes in large-scale models under free convection , 1995 .

[28]  Bri-Mathias Hodge,et al.  The Wind Integration National Dataset (WIND) Toolkit , 2015 .

[29]  G. Thompson,et al.  Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization , 2008 .

[30]  C. Soares,et al.  Wind resource assessment offshore the Atlantic Iberian coast with the WRF model , 2018 .

[31]  Moncho Gómez-Gesteira,et al.  Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula , 2014 .

[32]  Axel Schweiger,et al.  Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic , 2014 .

[33]  James G Brasseur,et al.  Non-steady wind turbine response to daytime atmospheric turbulence , 2017, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[34]  J. Michalakes,et al.  A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics , 2012 .

[35]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[36]  Walter Musial,et al.  Offshore Wind Energy Resource Assessment for Alaska , 2018 .