IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v9y2016i6p396-d70768.html
   My bibliography  Save this article

Statistical Analysis of Wave Climate Data Using Mixed Distributions and Extreme Wave Prediction

Author

Listed:
  • Wei Li

    (Division of Electricity, Department of Engineering Sciences, Swedish Centre for Electricity Energy Conversion, Uppsala University, Box 534, Uppsala SE-751 21, Sweden)

  • Jan Isberg

    (Division of Electricity, Department of Engineering Sciences, Swedish Centre for Electricity Energy Conversion, Uppsala University, Box 534, Uppsala SE-751 21, Sweden)

  • Rafael Waters

    (Division of Electricity, Department of Engineering Sciences, Swedish Centre for Electricity Energy Conversion, Uppsala University, Box 534, Uppsala SE-751 21, Sweden)

  • Jens Engström

    (Division of Electricity, Department of Engineering Sciences, Swedish Centre for Electricity Energy Conversion, Uppsala University, Box 534, Uppsala SE-751 21, Sweden)

  • Olle Svensson

    (Division of Electricity, Department of Engineering Sciences, Swedish Centre for Electricity Energy Conversion, Uppsala University, Box 534, Uppsala SE-751 21, Sweden)

  • Mats Leijon

    (Division of Electricity, Department of Engineering Sciences, Swedish Centre for Electricity Energy Conversion, Uppsala University, Box 534, Uppsala SE-751 21, Sweden)

Abstract

The investigation of various aspects of the wave climate at a wave energy test site is essential for the development of reliable and efficient wave energy conversion technology. This paper presents studies of the wave climate based on nine years of wave observations from the 2005–2013 period measured with a wave measurement buoy at the Lysekil wave energy test site located off the west coast of Sweden. A detailed analysis of the wave statistics is investigated to reveal the characteristics of the wave climate at this specific test site. The long-term extreme waves are estimated from applying the Peak over Threshold (POT) method on the measured wave data. The significant wave height and the maximum wave height at the test site for different return periods are also compared. In this study, a new approach using a mixed-distribution model is proposed to describe the long-term behavior of the significant wave height and it shows an impressive goodness of fit to wave data from the test site. The mixed-distribution model is also applied to measured wave data from four other sites and it provides an illustration of the general applicability of the proposed model. The methodologies used in this paper can be applied to general wave climate analysis of wave energy test sites to estimate extreme waves for the survivability assessment of wave energy converters and characterize the long wave climate to forecast the wave energy resource of the test sites and the energy production of the wave energy converters.

Suggested Citation

  • Wei Li & Jan Isberg & Rafael Waters & Jens Engström & Olle Svensson & Mats Leijon, 2016. "Statistical Analysis of Wave Climate Data Using Mixed Distributions and Extreme Wave Prediction," Energies, MDPI, vol. 9(6), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:6:p:396-:d:70768
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/9/6/396/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/9/6/396/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Waters, Rafael & Engström, Jens & Isberg, Jan & Leijon, Mats, 2009. "Wave climate off the Swedish west coast," Renewable Energy, Elsevier, vol. 34(6), pages 1600-1606.
    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. Yue Hong & Irina Temiz & Jianfei Pan & Mikael Eriksson & Cecilia Boström, 2021. "Damping Studies on PMLG-Based Wave Energy Converter under Oceanic Wave Climates," Energies, MDPI, vol. 14(4), pages 1-21, February.
    2. Andrea Farkas & Nastia Degiuli & Ivana Martić, 2019. "Assessment of Offshore Wave Energy Potential in the Croatian Part of the Adriatic Sea and Comparison with Wind Energy Potential," Energies, MDPI, vol. 12(12), pages 1-20, June.

    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. Dina Silva & Eugen Rusu & Carlos Guedes Soares, 2013. "Evaluation of Various Technologies for Wave Energy Conversion in the Portuguese Nearshore," Energies, MDPI, vol. 6(3), pages 1-21, March.
    2. 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.
    3. Brenda Rojas-Delgado & Monica Alonso & Hortensia Amaris & Juan de Santiago, 2019. "Wave Power Output Smoothing through the Use of a High-Speed Kinetic Buffer," Energies, MDPI, vol. 12(11), pages 1-28, June.
    4. Pasquale Contestabile & Vincenzo Ferrante & Diego Vicinanza, 2015. "Wave Energy Resource along the Coast of Santa Catarina (Brazil)," Energies, MDPI, vol. 8(12), pages 1-25, December.
    5. Iglesias, G. & Carballo, R., 2010. "Wave energy and nearshore hot spots: The case of the SE Bay of Biscay," Renewable Energy, Elsevier, vol. 35(11), pages 2490-2500.
    6. Yue Hong & Mikael Eriksson & Cecilia Boström & Rafael Waters, 2016. "Impact of Generator Stroke Length on Energy Production for a Direct Drive Wave Energy Converter," Energies, MDPI, vol. 9(9), pages 1-12, September.
    7. 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.
    8. Venugopalan Kurupath & Rickard Ekström & Mats Leijon, 2013. "Optimal Constant DC Link Voltage Operation of a Wave Energy Converter," Energies, MDPI, vol. 6(4), pages 1-14, April.
    9. Liberti, Luca & Carillo, Adriana & Sannino, Gianmaria, 2013. "Wave energy resource assessment in the Mediterranean, the Italian perspective," Renewable Energy, Elsevier, vol. 50(C), pages 938-949.
    10. Rusu, Liliana & Guedes Soares, C., 2012. "Wave energy assessments in the Azores islands," Renewable Energy, Elsevier, vol. 45(C), pages 183-196.
    11. Pasquale Contestabile & Enrico Di Lauro & Paolo Galli & Cesare Corselli & Diego Vicinanza, 2017. "Offshore Wind and Wave Energy Assessment around Malè and Magoodhoo Island (Maldives)," Sustainability, MDPI, vol. 9(4), pages 1-24, April.
    12. Liang, Bingchen & Fan, Fei & Liu, Fushun & Gao, Shanhong & Zuo, Hongyan, 2014. "22-Year wave energy hindcast for the China East Adjacent Seas," Renewable Energy, Elsevier, vol. 71(C), pages 200-207.
    13. Aydoğan, Burak & Ayat, Berna & Yüksel, Yalçın, 2013. "Black Sea wave energy atlas from 13 years hindcasted wave data," Renewable Energy, Elsevier, vol. 57(C), pages 436-447.
    14. Kim, Gunwoo & Jeong, Weon Mu & Lee, Kwang Soo & Jun, Kicheon & Lee, Myung Eun, 2011. "Offshore and nearshore wave energy assessment around the Korean Peninsula," Energy, Elsevier, vol. 36(3), pages 1460-1469.
    15. Bozzi, Silvia & Archetti, Renata & Passoni, Giuseppe, 2014. "Wave electricity production in Italian offshore: A preliminary investigation," Renewable Energy, Elsevier, vol. 62(C), pages 407-416.
    16. 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.
    17. Rusu, Eugen & Guedes Soares, C., 2013. "Coastal impact induced by a Pelamis wave farm operating in the Portuguese nearshore," Renewable Energy, Elsevier, vol. 58(C), pages 34-49.
    18. Yue Hong & Mikael Eriksson & Cecilia Boström & Jianfei Pan & Yun Liu & Rafael Waters, 2020. "Damping Effect Coupled with the Internal Translator Mass of Linear Generator-Based Wave Energy Converters," Energies, MDPI, vol. 13(17), pages 1-14, August.
    19. 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.
    20. Sierra, J.P. & González-Marco, D. & Sospedra, J. & Gironella, X. & Mösso, C. & Sánchez-Arcilla, A., 2013. "Wave energy resource assessment in Lanzarote (Spain)," Renewable Energy, Elsevier, vol. 55(C), pages 480-489.

    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:gam:jeners:v:9:y:2016:i:6:p:396-:d:70768. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.