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Wave exploitability index and wave resource classification

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  • Martinez, A.
  • Iglesias, G.

Abstract

The selection of areas for wave energy development requires a thorough characterisation of the resource. For all its importance, wave power should not be the only criterion, and overly emphasising its role to the detriment of other aspects may mislead developers to the wrong areas. In this work, a new approach is presented based on a combination of two elements: the Wave Exploitability Index (WEI), defined ad hoc, and a classification of the resource based on mean wave power. These elements are applied at a global scale using the ERA-5 database, which spans the period 1979–2019. The highest WEI values (0.14–0.22) are found to occur in the Tropics and mid-latitudes, which highlights their potential for wave energy exploitation. The lowest WEI values (below 0.06) are located in (semi)-enclosed seas, such as the Mediterranean Sea or the Gulf of Mexico. As regards the classification of the resource, Classes IV and V, with mean wave power over 40 kWm−1, occur in areas which have aroused great interest but which often do not have high WEI values due to the resource variability (e.g., Western Europe); these areas are hardly ideal from the resource standpoint. Class I (below 10 kWm−1), typical of enclosed seas, is of little interest. Finally, Classes II and III (10–40 kWm−1) occur in areas open to the ocean in the lower and lower-middle latitudes (e.g., Chile, SW Australia); they present the highest WEI values, thus showing great potential, and have received scant attention so far.

Suggested Citation

  • Martinez, A. & Iglesias, G., 2020. "Wave exploitability index and wave resource classification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
  • Handle: RePEc:eee:rensus:v:134:y:2020:i:c:s136403212030681x
    DOI: 10.1016/j.rser.2020.110393
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    Cited by:

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    5. Choupin, Ophelie & Del Río-Gamero, B. & Schallenberg-Rodríguez, Julieta & Yánez-Rosales, Pablo, 2022. "Integration of assessment-methods for wave renewable energy: Resource and installation feasibility," Renewable Energy, Elsevier, vol. 185(C), pages 455-482.
    6. Kamranzad, Bahareh & Lin, Pengzhi & Iglesias, Gregorio, 2021. "Combining methodologies on the impact of inter and intra-annual variation of wave energy on selection of suitable location and technology," Renewable Energy, Elsevier, vol. 172(C), pages 697-713.
    7. Bingölbali, Bilal & Majidi, Ajab Gul & Akpınar, Adem, 2021. "Inter- and intra-annual wave energy resource assessment in the south-western Black Sea coast," Renewable Energy, Elsevier, vol. 169(C), pages 809-819.
    8. Zheng, Chong-wei & Wu, Di & Wu, Hai-lang & Guo, Jing & Shen, Chong & Tian, Chuan & Tian, Xin-long & Xiao, Zi-niu & Zhou, Wen & Li, Chong-yin, 2022. "Propagation and attenuation of swell energy in the Pacific Ocean," Renewable Energy, Elsevier, vol. 188(C), pages 750-764.
    9. Zheng, Chong-wei, 2021. "Dynamic self-adjusting classification for global wave energy resources under different requirements," Energy, Elsevier, vol. 236(C).
    10. Majidi, AjabGul & Bingölbali, Bilal & Akpınar, Adem & Iglesias, Gregorio & Jafali, Halid, 2021. "Downscaling wave energy converters for optimum performance in low-energy seas," Renewable Energy, Elsevier, vol. 168(C), pages 705-722.
    11. Rusu, Liliana, 2022. "The near future expected wave power in the coastal environment of the Iberian Peninsula," Renewable Energy, Elsevier, vol. 195(C), pages 657-669.
    12. Ulazia, Alain & Saenz-Aguirre, Aitor & Ibarra-Berastegui, Gabriel & Sáenz, Jon & Carreno-Madinabeitia, Sheila & Esnaola, Ganix, 2023. "Performance variations of wave energy converters due to global long-term wave period change (1900–2010)," Energy, Elsevier, vol. 268(C).
    13. Zheng, Chong-wei & Li, Xue-hong & Azorin-Molina, Cesar & Li, Chong-yin & Wang, Qing & Xiao, Zi-niu & Yang, Shao-bo & Chen, Xuan & Zhan, Chao, 2022. "Global trends in oceanic wind speed, wind-sea, swell, and mixed wave heights," Applied Energy, Elsevier, vol. 321(C).
    14. Chongwei Zheng, 2023. "An Overview and Countermeasure of Global Wave Energy Classification," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    15. Shao, Zhuxiao & Gao, Huijun & Liang, Bingchen & Lee, Dongyoung, 2022. "Potential, trend and economic assessments of global wave power," Renewable Energy, Elsevier, vol. 195(C), pages 1087-1102.
    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).

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