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Wave Climate Resource Analysis Based on a Revised Gamma Spectrum for Wave Energy Conversion Technology

Author

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  • Jeremiah Pastor

    (Department of Mechanical Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

  • Yucheng Liu

    (Department of Mechanical Engineering, Mississippi State University, Mississippi State, MS 39760, USA)

Abstract

In order to correctly predict and evaluate the response of wave energy converters (WECs), an accurate representation of wave climate resource is crucial. This paper gives an overview of wave resource modeling techniques and applies a methodology to estimate the naturally available and technically recoverable resource in a given deployment site. The methodology was initially developed by the Electric Power Research Institute (EPRI), which uses a modified gamma spectrum to interpret sea state hindcast parameter data produced by National Oceanic and Atmospheric Administration’s (NOAA’s) WaveWatch III. This gamma spectrum is dependent on the calibration of two variables relating to the spectral width parameter and spectral peakedness parameter. In this study, this methodology was revised by the authors to increase its accuracy in formulating wavelength. The revised methodology shows how to assess a given geographic area’s wave resource based on its wave power density and total annual wave energy flux.

Suggested Citation

  • Jeremiah Pastor & Yucheng Liu, 2016. "Wave Climate Resource Analysis Based on a Revised Gamma Spectrum for Wave Energy Conversion Technology," Sustainability, MDPI, vol. 8(12), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:12:p:1321-:d:85166
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    References listed on IDEAS

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    Cited by:

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    3. Diego Vicinanza & Mariano Buccino, 2017. "A Helicopter View of the Special Issue on Wave Energy Converters," Sustainability, MDPI, vol. 9(2), pages 1-4, February.
    4. 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.
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    7. Florin Onea & Liliana Rusu, 2017. "A Long-Term Assessment of the Black Sea Wave Climate," Sustainability, MDPI, vol. 9(10), pages 1-18, October.
    8. Vázquez, Rubén & Cabos, William & Nieto-Borge, José Carlos & Gutiérrez, Claudia, 2024. "Complementarity of offshore energy resources on the Spanish coasts: Wind, wave, and photovoltaic energy," Renewable Energy, Elsevier, vol. 224(C).
    9. Egidijus Kasiulis & Jens Peter Kofoed & Arvydas Povilaitis & Algirdas Radzevičius, 2017. "Spatial Distribution of the Baltic Sea Near-Shore Wave Power Potential along the Coast of Klaipėda, Lithuania," Energies, MDPI, vol. 10(12), pages 1-18, December.
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    11. 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).
    12. Zhu, Kai & Shi, Hongda & Michele, Simone & Han, Meng & Cao, Feifei, 2024. "Analytical study on dynamic performance of a hybrid system in real sea states," Energy, Elsevier, vol. 290(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.
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    15. Zhu, Kai & Cao, Feifei & Wang, Tianyuan & Tao, Ji & Wei, Zhiwen & Shi, Hongda, 2024. "A comparative investigation into the dynamic performance of multiple wind-wave hybrid systems utilizing a full-process analytical model," Applied Energy, Elsevier, vol. 360(C).
    16. Nikon Vidjajev & Riina Palu & Jan Terentjev & Olli-Pekka Hilmola & Victor Alari, 2022. "Assessment of the Development Limitations for Wave Energy Utilization in the Baltic Sea," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
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    18. Christopher Stokes & Daniel C. Conley, 2018. "Modelling Offshore Wave farms for Coastal Process Impact Assessment: Waves, Beach Morphology, and Water Users," Energies, MDPI, vol. 11(10), pages 1-26, September.

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