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A practical method for modeling temporally-averaged ocean wave frequency-directional spectra for characterizing wave energy climates

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  • Ahn, Seongho
  • Neary, Vincent S.
  • Ha, Taemin

Abstract

Wave energy resource characterization investigations have been hindered because frequency-directional wave spectra are not broadly available for many coastal regions due to the insufficient spatial coverage of buoy observation networks and spectral wave model hindcast outputs. We address this problem by developing and validating a practical method for approximating temporally-averaged frequency-directional wave spectra averaged over periods of months or years from bulk wave parameters, which are available at a much greater coverage and resolution than frequency-directional wave spectra. While the temporally averaged frequency-directional wave spectrum over these periods cannot be used for analyzing a single sea state, it aggregates multiple sea states, identifies dominant wave energy systems representing wave climate, and resolves their spectral characteristics. Therefore, modelling temporally averaged frequency-directional wave spectra is of great value for planning and designing wave energy projects, e.g., resource characterization, site assessment, and conceptual design of wave energy converters. Temporally-averaged frequency-directional wave spectra and related important wave energy parameters approximated using this method are found to be more accurate than commonly used parametric wave spectrum models. This method can be applied to a wide range of wave climates given its universality and high accuracy. Also, the availability of bulk wave parameters from multi-decade high-resolution wave model hindcasts is increasing.

Suggested Citation

  • Ahn, Seongho & Neary, Vincent S. & Ha, Taemin, 2023. "A practical method for modeling temporally-averaged ocean wave frequency-directional spectra for characterizing wave energy climates," Renewable Energy, Elsevier, vol. 207(C), pages 499-511.
    • Handle: RePEc:eee:renene:v:207:y:2023:i:c:p:499-511
    DOI: 10.1016/j.renene.2023.03.034
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    References listed on IDEAS

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    1. Yang, Zhaoqing & García-Medina, Gabriel & Wu, Wei-Cheng & Wang, Taiping, 2020. "Characteristics and variability of the nearshore wave resource on the U.S. West Coast," Energy, Elsevier, vol. 203(C).
    2. Borja G. Reguero & Iñigo J. Losada & Fernando J. Méndez, 2019. "A recent increase in global wave power as a consequence of oceanic warming," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    3. Ahn, Seongho & Haas, Kevin A. & Neary, Vincent S., 2019. "Wave energy resource classification system for US coastal waters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 54-68.
    4. Reguero, B.G. & Losada, I.J. & Méndez, F.J., 2015. "A global wave power resource and its seasonal, interannual and long-term variability," Applied Energy, Elsevier, vol. 148(C), pages 366-380.
    5. Ahn, Seongho & Neary, Vincent S. & Allahdadi, Mohammad Nabi & He, Ruoying, 2021. "Nearshore wave energy resource characterization along the East Coast of the United States," Renewable Energy, Elsevier, vol. 172(C), pages 1212-1224.
    6. Stopa, Justin E. & Filipot, Jean-François & Li, Ning & Cheung, Kwok Fai & Chen, Yi-Leng & Vega, Luis, 2013. "Wave energy resources along the Hawaiian Island chain," Renewable Energy, Elsevier, vol. 55(C), pages 305-321.
    7. García-Medina, Gabriel & Özkan-Haller, H. Tuba & Ruggiero, Peter, 2014. "Wave resource assessment in Oregon and southwest Washington, USA," Renewable Energy, Elsevier, vol. 64(C), pages 203-214.
    8. Seongho Ahn & Kevin A. Haas & Vincent S. Neary, 2020. "Dominant Wave Energy Systems and Conditional Wave Resource Characterization for Coastal Waters of the United States," Energies, MDPI, vol. 13(12), pages 1-26, June.
    9. Allahdadi, M. Nabi & Gunawan, Budi & Lai, Jonathan & He, Ruoying & Neary, Vincent S., 2019. "Development and validation of a regional-scale high-resolution unstructured model for wave energy resource characterization along the US East Coast," Renewable Energy, Elsevier, vol. 136(C), pages 500-511.
    10. Ahn, Seongho & Haas, Kevin A. & Neary, Vincent S., 2020. "Wave energy resource characterization and assessment for coastal waters of the United States," Applied Energy, Elsevier, vol. 267(C).
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