IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i14p2780-d249960.html
   My bibliography  Save this article

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

Author

Listed:
  • Jared A. Lee

    (Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, USA)

  • Paula Doubrawa

    (National Renewable Energy Laboratory, Golden, CO 80401, USA)

  • Lulin Xue

    (Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, USA)

  • Andrew J. Newman

    (Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, USA)

  • Caroline Draxl

    (National Renewable Energy Laboratory, Golden, CO 80401, USA)

  • George Scott

    (National Renewable Energy Laboratory, Golden, CO 80401, USA)

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 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.

Suggested Citation

  • Jared A. Lee & Paula Doubrawa & Lulin Xue & Andrew J. Newman & Caroline Draxl & George Scott, 2019. "Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set," Energies, MDPI, vol. 12(14), pages 1-22, July.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2780-:d:249960
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/14/2780/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/14/2780/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Draxl, Caroline & Clifton, Andrew & Hodge, Bri-Mathias & McCaa, Jim, 2015. "The Wind Integration National Dataset (WIND) Toolkit," Applied Energy, Elsevier, vol. 151(C), pages 355-366.
    2. Chancham, Chana & Waewsak, Jompob & Gagnon, Yves, 2017. "Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand," Energy, Elsevier, vol. 139(C), pages 706-731.
    3. Salvação, N. & Guedes Soares, C., 2018. "Wind resource assessment offshore the Atlantic Iberian coast with the WRF model," Energy, Elsevier, vol. 145(C), pages 276-287.
    4. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "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," Applied Energy, Elsevier, vol. 135(C), pages 234-246.
    5. Mattar, Cristian & Borvarán, Dager, 2016. "Offshore wind power simulation by using WRF in the central coast of Chile," Renewable Energy, Elsevier, vol. 94(C), pages 22-31.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sward, J.A. & Ault, T.R. & Zhang, K.M., 2023. "Spatial biases revealed by LiDAR in a multiphysics WRF ensemble designed for offshore wind," Energy, Elsevier, vol. 262(PA).
    2. Rober Mamani & Patrick Hendrick, 2022. "Wind Power Potential in Highlands of the Bolivian Andes: A Numerical Approach," Energies, MDPI, vol. 15(12), pages 1-16, June.
    3. Geovanni Hernández Galvez & Daniel Chuck Liévano & Omar Sarracino Martínez & Orlando Lastres Danguillecourt & José Rafael Dorrego Portela & Antonio Trujillo Narcía & Ricardo Saldaña Flores & Liliana P, 2022. "Harnessing Offshore Wind Energy along the Mexican Coastline in the Gulf of Mexico—An Exploratory Study including Sustainability Criteria," Sustainability, MDPI, vol. 14(10), pages 1-26, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    2. Minhyeop Kang & Kyungnam Ko & Minyeong Kim, 2020. "Verification of the Reliability of Offshore Wind Resource Prediction Using an Atmosphere–Ocean Coupled Model," Energies, MDPI, vol. 13(1), pages 1-15, January.
    3. Gil Ruiz, Samuel Andrés & Cañón Barriga, Julio Eduardo & Martínez, J. Alejandro, 2022. "Assessment and validation of wind power potential at convection-permitting resolution for the Caribbean region of Colombia," Energy, Elsevier, vol. 244(PB).
    4. Perini de Souza, Noele Bissoli & Sperandio Nascimento, Erick Giovani & Bandeira Santos, Alex Alisson & Moreira, Davidson Martins, 2022. "Wind mapping using the mesoscale WRF model in a tropical region of Brazil," Energy, Elsevier, vol. 240(C).
    5. Tuchtenhagen, Patrícia & Carvalho, Gilvani Gomes de & Martins, Guilherme & Silva, Pollyanne Evangelista da & Oliveira, Cristiano Prestrelo de & de Melo Barbosa Andrade, Lara & Araújo, João Medeiros de, 2020. "WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil," Energy, Elsevier, vol. 190(C).
    6. Liu, Yichao & Chen, Daoyi & Li, Sunwei & Chan, P.W., 2018. "Discerning the spatial variations in offshore wind resources along the coast of China via dynamic downscaling," Energy, Elsevier, vol. 160(C), pages 582-596.
    7. Salvação, N. & Guedes Soares, C., 2018. "Wind resource assessment offshore the Atlantic Iberian coast with the WRF model," Energy, Elsevier, vol. 145(C), pages 276-287.
    8. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2017. "Offshore winds and wind energy production estimates derived from ASCAT, OSCAT, numerical weather prediction models and buoys – A comparative study for the Iberian Peninsula Atlantic coast," Renewable Energy, Elsevier, vol. 102(PB), pages 433-444.
    9. Christina Ortega & Amin Younes & Mark Severy & Charles Chamberlin & Arne Jacobson, 2020. "Resource and Load Compatibility Assessment of Wind Energy Offshore of Humboldt County, California," Energies, MDPI, vol. 13(21), pages 1-27, October.
    10. Rusu, Eugen & Onea, Florin, 2019. "A parallel evaluation of the wind and wave energy resources along the Latin American and European coastal environments," Renewable Energy, Elsevier, vol. 143(C), pages 1594-1607.
    11. González-Alonso de Linaje, N. & Mattar, C. & Borvarán, D., 2019. "Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile," Energy, Elsevier, vol. 188(C).
    12. Dong, Cong & Huang, Guohe (Gordon) & Cheng, Guanhui, 2021. "Offshore wind can power Canada," Energy, Elsevier, vol. 236(C).
    13. Archer, C.L. & Simão, H.P. & Kempton, W. & Powell, W.B. & Dvorak, M.J., 2017. "The challenge of integrating offshore wind power in the U.S. electric grid. Part I: Wind forecast error," Renewable Energy, Elsevier, vol. 103(C), pages 346-360.
    14. Dayal, Kunal K. & Bellon, Gilles & Cater, John E. & Kingan, Michael J. & Sharma, Rajnish N., 2021. "High-resolution mesoscale wind-resource assessment of Fiji using the Weather Research and Forecasting (WRF) model," Energy, Elsevier, vol. 232(C).
    15. Duarte Jacondino, William & Nascimento, Ana Lucia da Silva & Calvetti, Leonardo & Fisch, Gilberto & Augustus Assis Beneti, Cesar & da Paz, Sheila Radman, 2021. "Hourly day-ahead wind power forecasting at two wind farms in northeast Brazil using WRF model," Energy, Elsevier, vol. 230(C).
    16. Li, Jiale & Yu, Xiong (Bill), 2018. "Onshore and offshore wind energy potential assessment near Lake Erie shoreline: A spatial and temporal analysis," Energy, Elsevier, vol. 147(C), pages 1092-1107.
    17. Chen, Xinping & Foley, Aoife & Zhang, Zenghai & Wang, Kaimin & O'Driscoll, Kieran, 2020. "An assessment of wind energy potential in the Beibu Gulf considering the energy demands of the Beibu Gulf Economic Rim," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    18. Costoya, X. & deCastro, M. & Carvalho, D. & Gómez-Gesteira, M., 2020. "On the suitability of offshore wind energy resource in the United States of America for the 21st century," Applied Energy, Elsevier, vol. 262(C).
    19. Argüeso, D. & Businger, S., 2018. "Wind power characteristics of Oahu, Hawaii," Renewable Energy, Elsevier, vol. 128(PA), pages 324-336.
    20. Florin Onea & Liliana Rusu, 2018. "Evaluation of Some State-Of-The-Art Wind Technologies in the Nearshore of the Black Sea," Energies, MDPI, vol. 11(9), pages 1-16, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2780-:d:249960. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.