IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v136y2019icp500-511.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148119300175
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2019.01.020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bento, A. Rute & Martinho, Paulo & Guedes Soares, C., 2018. "Wave energy assessement for Northern Spain from a 33-year hindcast," Renewable Energy, Elsevier, vol. 127(C), pages 322-333.
    2. Yang, Zhaoqing & Neary, Vincent S. & Wang, Taiping & Gunawan, Budi & Dallman, Annie R. & Wu, Wei-Cheng, 2017. "A wave model test bed study for wave energy resource characterization," Renewable Energy, Elsevier, vol. 114(PA), pages 132-144.
    3. 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.
    4. Defne, Zafer & Haas, Kevin A. & Fritz, Hermann M., 2009. "Wave power potential along the Atlantic coast of the southeastern USA," Renewable Energy, Elsevier, vol. 34(10), pages 2197-2205.
    5. Morim, Joao & Cartwright, Nick & Etemad-Shahidi, Amir & Strauss, Darrell & Hemer, Mark, 2016. "Wave energy resource assessment along the Southeast coast of Australia on the basis of a 31-year hindcast," Applied Energy, Elsevier, vol. 184(C), pages 276-297.
    6. Ramos, V. & Ringwood, John V., 2016. "Exploring the utility and effectiveness of the IEC (International Electrotechnical Commission) wave energy resource assessment and characterisation standard: A case study," Energy, Elsevier, vol. 107(C), pages 668-682.
    7. Gunn, Kester & Stock-Williams, Clym, 2012. "Quantifying the global wave power resource," Renewable Energy, Elsevier, vol. 44(C), pages 296-304.
    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. Li, Ning & García Medina, Gabriel & Yang, Zhaoqing & Cheung, Kwok Fai & Hitzl, David & Chen, Yi-Leng, 2023. "Wave climate and energy resources in the Mariana Islands from a 42-year high-resolution hindcast," Renewable Energy, Elsevier, vol. 215(C).
    2. 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).
    3. Tunde Aderinto & Hua Li, 2020. "Effect of Spatial and Temporal Resolution Data on Design and Power Capture of a Heaving Point Absorber," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    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.
    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.

    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. Lin, Yifan & Dong, Sheng & Wang, Zhifeng & Guedes Soares, C., 2019. "Wave energy assessment in the China adjacent seas on the basis of a 20-year SWAN simulation with unstructured grids," Renewable Energy, Elsevier, vol. 136(C), pages 275-295.
    2. 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).
    3. 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).
    4. Chen, Xinping & Wang, Kaimin & Zhang, Zenghai & Zeng, Yindong & Zhang, Yao & O'Driscoll, Kieran, 2017. "An assessment of wind and wave climate as potential sources of renewable energy in the nearshore Shenzhen coastal zone of the South China Sea," Energy, Elsevier, vol. 134(C), pages 789-801.
    5. Kilcher, Levi & García Medina, Gabriel & Yang, Zhaoqing, 2023. "A scalable wave resource assessment methodology: Application to U.S. waters," Renewable Energy, Elsevier, vol. 217(C).
    6. 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.
    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. Yaakob, Omar & Hashim, Farah Ellyza & Mohd Omar, Kamaludin & Md Din, Ami Hassan & Koh, Kho King, 2016. "Satellite-based wave data and wave energy resource assessment for South China Sea," Renewable Energy, Elsevier, vol. 88(C), pages 359-371.
    9. Sanil Kumar, V. & Anoop, T.R., 2015. "Wave energy resource assessment for the Indian shelf seas," Renewable Energy, Elsevier, vol. 76(C), pages 212-219.
    10. 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.
    11. 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.
    12. Gonçalves, Marta & Martinho, Paulo & Guedes Soares, C., 2020. "Wave energy assessment based on a 33-year hindcast for the Canary Islands," Renewable Energy, Elsevier, vol. 152(C), pages 259-269.
    13. Guillou, Nicolas & Chapalain, Georges, 2018. "Annual and seasonal variabilities in the performances of wave energy converters," Energy, Elsevier, vol. 165(PB), pages 812-823.
    14. Zhou, Guoqing & Huang, Jingjin & Zhang, Guangyun, 2015. "Evaluation of the wave energy conditions along the coastal waters of Beibu Gulf, China," Energy, Elsevier, vol. 85(C), pages 449-457.
    15. Silva, Dina & Martinho, Paulo & Guedes Soares, C., 2018. "Wave energy distribution along the Portuguese continental coast based on a thirty three years hindcast," Renewable Energy, Elsevier, vol. 127(C), pages 1064-1075.
    16. Tunde Aderinto & Hua Li, 2020. "Effect of Spatial and Temporal Resolution Data on Design and Power Capture of a Heaving Point Absorber," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    17. Cuttler, Michael V.W. & Hansen, Jeff E. & Lowe, Ryan J., 2020. "Seasonal and interannual variability of the wave climate at a wave energy hotspot off the southwestern coast of Australia," Renewable Energy, Elsevier, vol. 146(C), pages 2337-2350.
    18. Soomere, Tarmo & Eelsalu, Maris, 2014. "On the wave energy potential along the eastern Baltic Sea coast," Renewable Energy, Elsevier, vol. 71(C), pages 221-233.
    19. Rosa-Santos, Paulo & Taveira-Pinto, Francisco & Rodríguez, Claudio A. & Ramos, Victor & López, Mario, 2019. "The CECO wave energy converter: Recent developments," Renewable Energy, Elsevier, vol. 139(C), pages 368-384.
    20. 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.

    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:eee:renene:v:136:y:2019:i:c:p:500-511. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.