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Wave energy resource characterization employing joint distributions in frequency-direction-time domain

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  • Ahn, Seongho
  • Neary, Vincent S.

Abstract

Joint and marginal distributions in the frequency, direction, and time domain are employed to demonstrate their value for wave energy resource characterization when full spectra are available. Insights gained through analysis of these distributions support wave energy converter concept design, operation and maintenance. Spatial trends in the wave energy resource and contributing wave energy systems along the continental shelf of the West Coast of the United States are investigated using the most recent two-dimensional wave spectra measurements at four buoys over an eleven year period (2008 to 2018). Resource hot spots and dominant resolved energy resource bands in the frequency-direction-time domain are delineated. Resource attributes, including frequency and directional spreading, and seasonal variability, are characterized using joint distributions and marginal distributions of wave power spectra. North Pacific westerly swells in the winter season, augmented by Aleutian low-pressure southwesterly swells, are the principal suppliers of the dominant resource and main drivers influencing resource attributes. The modification of these systems southward, especially the North Pacific westerly swells, explains the observed spatial resource trends. The dominant resource wave period shifts two seconds to higher wave periods, thirty degrees in the dominant direction band to a more northward orientation, and forward by one month.

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  • Ahn, Seongho & Neary, Vincent S., 2021. "Wave energy resource characterization employing joint distributions in frequency-direction-time domain," Applied Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:appene:v:285:y:2021:i:c:s0306261920317761
    DOI: 10.1016/j.apenergy.2020.116407
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    References listed on IDEAS

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    1. 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.
    2. Haces-Fernandez, Francisco & Li, Hua & Ramirez, David, 2018. "Wave energy characterization and assessment in the U.S. Gulf of Mexico, East and West Coasts with Energy Event concept," Renewable Energy, Elsevier, vol. 123(C), pages 312-322.
    3. 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).
    4. Lenee-Bluhm, Pukha & Paasch, Robert & Özkan-Haller, H. Tuba, 2011. "Characterizing the wave energy resource of the US Pacific Northwest," Renewable Energy, Elsevier, vol. 36(8), pages 2106-2119.
    5. 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).
    6. 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.
    7. Wu, Wei-Cheng & Wang, Taiping & Yang, Zhaoqing & García-Medina, Gabriel, 2020. "Development and validation of a high-resolution regional wave hindcast model for U.S. West Coast wave resource characterization," Renewable Energy, Elsevier, vol. 152(C), pages 736-753.
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    Cited by:

    1. Ahn, Seongho & Neary, Vincent S. & Haas, Kevin A., 2022. "Global wave energy resource classification system for regional energy planning and project development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    2. Adedoyin Isola Lawal, 2023. "The Nexus between Economic Growth, Energy Consumption, Agricultural Output, and CO 2 in Africa: Evidence from Frequency Domain Estimates," Energies, MDPI, vol. 16(3), pages 1-27, January.
    3. 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.
    4. Shao, Zhuxiao & Gao, Huijun & Liang, Bingchen & Lee, Dongyoung, 2022. "Potential, trend and economic assessments of global wave power," Renewable Energy, Elsevier, vol. 195(C), pages 1087-1102.

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