IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v27y2013icp244-257.html
   My bibliography  Save this article

The assessment of extreme wave analysis methods applied to potential marine energy sites using numerical model data

Author

Listed:
  • Agarwal, Atul
  • Venugopal, Vengatesan
  • Harrison, Gareth P.

Abstract

The accurate estimation of extreme conditions, such as 100-yr return levels of significant wave height is an important aspect in the design of marine energy converters, offshore and coastal structures. This study investigates the different approaches for the estimation of extreme waves that have been applied in the past, and determines the 100-yr return levels using the high resolution ERA-Interim dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). It is demonstrated in the paper that fitting a Generalized Pareto Distribution to all exceedances over a high threshold is the most suitable approach. The estimates thus obtained are compared with previously computed estimates for buoys and offshore platforms. The effect of duration of data on the estimates is also investigated. Finally, a 100-yr return level map for the North Atlantic region is presented.

Suggested Citation

  • Agarwal, Atul & Venugopal, Vengatesan & Harrison, Gareth P., 2013. "The assessment of extreme wave analysis methods applied to potential marine energy sites using numerical model data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 244-257.
    • Handle: RePEc:eee:rensus:v:27:y:2013:i:c:p:244-257
    DOI: 10.1016/j.rser.2013.06.049
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032113004401
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2013.06.049?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. Wimmer, Werenfrid & Challenor, Peter & Retzler, Chris, 2006. "Extreme wave heights in the North Atlantic from Altimeter Data," Renewable Energy, Elsevier, vol. 31(2), pages 241-248.
    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. Benjamins, Steven & Williamson, Benjamin & Billing, Suzannah-Lynn & Yuan, Zhiming & Collu, Maurizio & Fox, Clive & Hobbs, Laura & Masden, Elizabeth A. & Cottier-Cook, Elizabeth J. & Wilson, Ben, 2024. "Potential environmental impacts of floating solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    2. Hashim, Roslan & Roy, Chandrabhushan & Motamedi, Shervin & Shamshirband, Shahaboddin & Petković, Dalibor, 2016. "Selection of climatic parameters affecting wave height prediction using an enhanced Takagi-Sugeno-based fuzzy methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 246-257.
    3. Lavidas, George, 2020. "Selection index for Wave Energy Deployments (SIWED): A near-deterministic index for wave energy converters," Energy, Elsevier, vol. 196(C).
    4. Zheng, Chong Wei & Wang, Qing & Li, Chong Yin, 2017. "An overview of medium- to long-term predictions of global wave energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1492-1502.
    5. 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).
    6. Jessica Borges Posterari & Takuji Waseda, 2022. "Wave Energy in the Pacific Island Countries: A New Integrative Conceptual Framework for Potential Challenges in Harnessing Wave Energy," Energies, MDPI, vol. 15(7), pages 1-24, April.

    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. Cornejo-Bueno, L. & Nieto-Borge, J.C. & García-Díaz, P. & Rodríguez, G. & Salcedo-Sanz, S., 2016. "Significant wave height and energy flux prediction for marine energy applications: A grouping genetic algorithm – Extreme Learning Machine approach," Renewable Energy, Elsevier, vol. 97(C), pages 380-389.
    2. Larsén, Xiaoli Guo & Kalogeri, Christina & Galanis, George & Kallos, George, 2015. "A statistical methodology for the estimation of extreme wave conditions for offshore renewable applications," Renewable Energy, Elsevier, vol. 80(C), pages 205-218.

    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:27:y:2013:i:c:p:244-257. 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.