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Development and validation of a regional-scale high-resolution unstructured model for wave energy resource characterization along the US East Coast

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  • Allahdadi, M. Nabi
  • Gunawan, Budi
  • Lai, Jonathan
  • He, Ruoying
  • Neary, Vincent S.

Abstract

Leveraging the high-performance computing capability at one of the US Department of Energy’s (USDOE) National Laboratories, an ultra-high-resolution Simulating WAves Nearshore (SWAN) model suitable for wave energy project feasibility studies is developed for the US East Coast Region. This model uses an unstructured mesh with a coastal resolution of 200 m. It is forced by Climate Forecast System Reanalysis wind fields with spatial and temporal resolutions of 0.312° and 1 h at the surface, and by wave parameters from the global WAVEWATCH III model along the model’s open boundaries. It is the first USDOE regional wave hindcast model for the US East Coast developed according to International Electrotechnical Commission standards for wave energy resource assessment and characterization. The present study focuses on the development and validation of this ultra-high resolution large-scale model, including source model selection, sensitivity studies, and model performance evaluation for a wave energy resource characterization application.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:136:y:2019:i:c:p:500-511
    DOI: 10.1016/j.renene.2019.01.020
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    5. Yang, Zhaoqing & García Medina, Gabriel & Neary, Vincent S. & Ahn, Seongho & Kilcher, Levi & Bharath, Aidan, 2023. "Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters," Renewable Energy, Elsevier, vol. 212(C), pages 803-817.
    6. García Medina, Gabriel & Yang, Zhaoqing & Li, Ning & Cheung, Kwok Fai & Lutu-McMoore, Elinor, 2023. "Wave climate and energy resources in American Samoa from a 42-year high-resolution hindcast," Renewable Energy, Elsevier, vol. 210(C), pages 604-617.
    7. Liliana Rusu & Eugen Rusu, 2021. "Evaluation of the Worldwide Wave Energy Distribution Based on ERA5 Data and Altimeter Measurements," Energies, MDPI, vol. 14(2), pages 1-16, January.
    8. Zhang, Na & Li, Shuai & Wu, Yongsheng & Wang, Keh-Han & Zhang, Qinghe & You, Zai-Jin & Wang, Jin, 2020. "Effects of sea ice on wave energy flux distribution in the Bohai Sea," Renewable Energy, Elsevier, vol. 162(C), pages 2330-2343.
    9. 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.
    10. Ribeiro, A.S. & deCastro, M. & Costoya, X. & Rusu, Liliana & Dias, J.M. & Gomez-Gesteira, M., 2021. "A Delphi method to classify wave energy resource for the 21st century: Application to the NW Iberian Peninsula," Energy, Elsevier, vol. 235(C).
    11. Li, Ning & García-Medina, Gabriel & Cheung, Kwok Fai & Yang, Zhaoqing, 2021. "Wave energy resources assessment for the multi-modal sea state of Hawaii," Renewable Energy, Elsevier, vol. 174(C), pages 1036-1055.
    12. Coe, Ryan G. & Ahn, Seongho & Neary, Vincent S. & Kobos, Peter H. & Bacelli, Giorgio, 2021. "Maybe less is more: Considering capacity factor, saturation, variability, and filtering effects of wave energy devices," Applied Energy, Elsevier, vol. 291(C).
    13. Guillou, Nicolas & Chapalain, Georges, 2020. "Assessment of wave power variability and exploitation with a long-term hindcast database," Renewable Energy, Elsevier, vol. 154(C), pages 1272-1282.
    14. Joensen, Bárður & Niclasen, Bárður A. & Bingham, Harry B., 2021. "Wave power assessment in Faroese waters using an oceanic to nearshore scale spectral wave model," Energy, Elsevier, vol. 235(C).
    15. 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.
    16. 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.

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