IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v104y2019icp54-68.html
   My bibliography  Save this article

Wave energy resource classification system for US coastal waters

Author

Listed:
  • Ahn, Seongho
  • Haas, Kevin A.
  • Neary, Vincent S.

Abstract

Energy resource classification systems are useful assessment tools that support energy planning and project development, e.g., siting and feasibility studies. They typically establish standard classes of power, a measure of the opportunity for energy resource capture. In this study, we develop wave energy resource classification systems for the US based on wave power (J, kW/m) and its distribution with peak period (Tp,s). These metrics are calculated for 70,386 sites from partitioned bulk wave parameters generated from a validated 30-year WaveWatch III model hindcast. As the operating resonant period bandwidth of a wave energy converter (WEC) technology is an important design characteristic, the dominant period band containing the largest energy content is identified among three peak period band classes. These classification systems, comprised of four power classes and three peak period band classes, are based on the total wave power or the partitioned wave power in the dominant peak period band. They discriminate distinct trends in wave energy resource among five regions within the US, and provide useful information for energy planners, project developers, and technology designers. They also establish a framework for investigating the feasibility of a compatible wave climate (design load) conditions and WEC technology classification system to reduce design and manufacturing costs.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:rensus:v:104:y:2019:i:c:p:54-68
    DOI: 10.1016/j.rser.2019.01.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032119300279
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2019.01.017?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. Arinaga, Randi A. & Cheung, Kwok Fai, 2012. "Atlas of global wave energy from 10 years of reanalysis and hindcast data," Renewable Energy, Elsevier, vol. 39(1), pages 49-64.
    2. Stopa, Justin E. & Cheung, Kwok Fai & Chen, Yi-Leng, 2011. "Assessment of wave energy resources in Hawaii," Renewable Energy, Elsevier, vol. 36(2), pages 554-567.
    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. 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.
    6. Beyene, Asfaw & Wilson, James H., 2006. "Comparison of wave energy flux for northern, central, and southern coast of California based on long-term statistical wave data," Energy, Elsevier, vol. 31(12), pages 1856-1869.
    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. 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. 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).
    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. Shahriar, Tanvir & Habib, M. Ahsan, 2024. "A reconnaissance-level characterization of wave energy resource in the exclusive economic zones of Bay-of-Bengal," Renewable Energy, Elsevier, vol. 225(C).
    6. 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).
    7. 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).
    8. Neary, Vincent S. & Ahn, Seongho, 2023. "Global atlas of extreme significant wave heights and relative risk ratios," Renewable Energy, Elsevier, vol. 208(C), pages 130-140.
    9. Shi, Xueli & Liang, Bingchen & Li, Shaowu & Zhao, Jianchun & Wang, Junhui & Wang, Zhenlu, 2024. "Wave energy resource classification system for the China East Adjacent Seas based on multivariate clustering," Energy, Elsevier, vol. 299(C).
    10. Robertson, Bryson & Bekker, Jessica & Buckham, Bradley, 2020. "Renewable integration for remote communities: Comparative allowable cost analyses for hydro, solar and wave energy," Applied Energy, Elsevier, vol. 264(C).
    11. 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.
    12. 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.
    13. Chongwei Zheng, 2023. "An Overview and Countermeasure of Global Wave Energy Classification," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    14. Milad Shadman & Corbiniano Silva & Daiane Faller & Zhijia Wu & Luiz Paulo de Freitas Assad & Luiz Landau & Carlos Levi & Segen F. Estefen, 2019. "Ocean Renewable Energy Potential, Technology, and Deployments: A Case Study of Brazil," Energies, MDPI, vol. 12(19), pages 1-37, September.
    15. Guillou, Nicolas, 2020. "Estimating wave energy flux from significant wave height and peak period," Renewable Energy, Elsevier, vol. 155(C), pages 1383-1393.
    16. Penalba, Markel & Aizpurua, Jose Ignacio & Martinez-Perurena, Ander & Iglesias, Gregorio, 2022. "A data-driven long-term metocean data forecasting approach for the design of marine renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    17. Fairley, Iain & Lewis, Matthew & Robertson, Bryson & Hemer, Mark & Masters, Ian & Horrillo-Caraballo, Jose & Karunarathna, Harshinie & Reeve, Dominic E., 2020. "A classification system for global wave energy resources based on multivariate clustering," Applied Energy, Elsevier, vol. 262(C).
    18. Ahn, Seongho & Neary, Vincent S., 2021. "Wave energy resource characterization employing joint distributions in frequency-direction-time domain," Applied Energy, Elsevier, vol. 285(C).

    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. 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. 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).
    3. 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.
    4. 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.
    5. 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.
    6. Sierra, J.P. & Mösso, C. & González-Marco, D., 2014. "Wave energy resource assessment in Menorca (Spain)," Renewable Energy, Elsevier, vol. 71(C), pages 51-60.
    7. 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.
    8. Mustapa, M.A. & Yaakob, O.B. & Ahmed, Yasser M. & Rheem, Chang-Kyu & Koh, K.K. & Adnan, Faizul Amri, 2017. "Wave energy device and breakwater integration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 43-58.
    9. Besio, G. & Mentaschi, L. & Mazzino, A., 2016. "Wave energy resource assessment in the Mediterranean Sea on the basis of a 35-year hindcast," Energy, Elsevier, vol. 94(C), pages 50-63.
    10. Muhammed Zafar Ali Khan & Haider Ali Khan & Muhammad Aziz, 2022. "Harvesting Energy from Ocean: Technologies and Perspectives," Energies, MDPI, vol. 15(9), pages 1-43, May.
    11. Zhou, Guoqing & Huang, Jingjin & Yue, Tao & Luo, Qingli & Zhang, Guangyun, 2015. "Temporal-spatial distribution of wave energy: A case study of Beibu Gulf, China," Renewable Energy, Elsevier, vol. 74(C), pages 344-356.
    12. Alonso, Rodrigo & Solari, Sebastián & Teixeira, Luis, 2015. "Wave energy resource assessment in Uruguay," Energy, Elsevier, vol. 93(P1), pages 683-696.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. Wang, Zhifeng & Dong, Sheng & Li, Xue & Guedes Soares, C., 2016. "Assessments of wave energy in the Bohai Sea, China," Renewable Energy, Elsevier, vol. 90(C), pages 145-156.
    18. 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.
    19. 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.
    20. Su, Wen-Ray & Chen, Hongey & Chen, Wei-Bo & Chang, Chih-Hsin & Lin, Lee-Yaw & Jang, Jiun-Huei & Yu, Yi-Chiang, 2018. "Numerical investigation of wave energy resources and hotspots in the surrounding waters of Taiwan," Renewable Energy, Elsevier, vol. 118(C), pages 814-824.

    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:rensus:v:104:y:2019:i:c:p:54-68. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.