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Temporal-Spatial Distribution of Wave Energy in the Maritime Silk Road

  • Chongwei ZhengEmail author
  • Jianjun Xu
  • Chao Zhan
  • Qing Wang
Chapter
Part of the Springer Oceanography book series (SPRINGEROCEAN)

Abstract

Previous researchers have made great contribution to the analysis of the wave energy climatic characteristics of many sea areas globally. But there are a few researches about the Maritime Silk Road. In the systematic aspect of the study of wave energy climatic characteristics, the elements of analysis are still not comprehensive enough. Besides considering traditional wave power density (WPD), energy stability, energy storage, it is necessary to take full consideration of the available rate, energy richness, energy direction, and the contribution of different sea states to wave energy, which are also closely related to the development of the wave energy. Scarce materials, large reserves and huge amount calculations and the high technical requirements have greatly increased the difficulty of systematic research on wave energy. For the first time, this chapter presented the spatio-temporal distribution characteristics of a series of key parameters of wave energy of the Maritime Silk Road by utilizing ERA-interim wave data from the ECMWF, to provide technical support (site selection, daily operation, etc.) for the development of resource such as wave power generation and seawater desalination.

Keywords

Maritime Silk Road Wave energy ERA-interim wave data Spatio-temporal distribution Wave power density Stability Energy storage Available rate Energy richness Energy direction 

References

  1. Akpamar A, Komurcu MI (2013) Assessment of wave energy resource of the Black Sea based on 15-year numerical hindcast data. Appl Energy 101:502–512CrossRefGoogle Scholar
  2. Alves JH (2006) Numerical modeling of ocean swell contributions to the global wind-wave climate. Ocean Model 11:98–122CrossRefGoogle Scholar
  3. Bao XH, Zhang FQ (2013) Evaluation of NCEP-CFSR, NCEP-NCAR, ERA-Interim, and ERA-40 reanalysis datasets against independent sounding observations over the Tibetan Plateau. J Clim 26:206–214CrossRefGoogle Scholar
  4. Bhowmick SA, Kumar R, Chaudhuri S, Sarkar A (2011) Swell propagation over Indian Ocean Region. Intl J Ocean Clim Syst 2(2):87–99CrossRefGoogle Scholar
  5. Bueno LC, Nieto-Borge JC, 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. Renew Energy 97:380–389CrossRefGoogle Scholar
  6. Cornett AM (2008) A global wave energy resource assessment. In: Proceedings of the eighteenth international offshore and polar engineering conference, Canada, 2008Google Scholar
  7. Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol Soc 137(656):553–597Google Scholar
  8. Iglesias G, Carballo R (2011) Choosing the site for the first wave farm in a region: a case study in the Galician Southwest (Spain). Energy 36(9):5525–5531CrossRefGoogle Scholar
  9. Kamranzad B, Etemad-Shahidi A, Chegini V, Yeganeh-Bakhtiary A (2015) Climate change impact on wave energy in the Persian Gulf. Ocean Dyn 65:777–794CrossRefGoogle Scholar
  10. Kamranzad B, Chegini V, Etemad-Shahidi A (2016) Temporal-spatial variation of wave energy and nearshore hotspots in the Gulf of Oman based on locally generated wind waves. Renew Energy 94:341–352CrossRefGoogle Scholar
  11. Langodan S, Viswanadhapalli Y, Dasari HP, Knio O, Hoteit I (2016) A high-resolution assessment of wind and wave energy potentials in the Red Sea. Appl Energy 181:244–255CrossRefGoogle Scholar
  12. Lenee-Bluhm P, Paasch R, Ozkan-Haller HT (2011) Characterizing the wave energy resource of the US Pacific Northwest. Renew Energy 36:2106–2119CrossRefGoogle Scholar
  13. Liang BC, Shao ZX, Wu YJ, Shi HD, Liu Z (2017) Numerical study of wave energy resources under wave-current interaction in the coastal area of Qingdao, China. Renew Energy 101:845–855CrossRefGoogle Scholar
  14. Reikard G, Robertson B, Buckham B, Bidlot JR, Hiles C (2015) Simulating and forecasting ocean wave energy in western Canada. Ocean Eng 103:223–236CrossRefGoogle Scholar
  15. Reikard G, Robertson B, Bidlot JR (2017) Wave energy worldwide: simulating wave farms, forecasting, and calculating reserves. Intl J Mar Energy 17:156–185CrossRefGoogle Scholar
  16. Ren JL, Luo YY, Zhong YJ (2008) The implementation for the analysis system of ocean wave resources and the application of wave energy power generation. J Zhejiang Univ Technol 36(2):186–191Google Scholar
  17. Ren JL, Luo YY, Chen JJ (2009) Research on wave power application by the information system for ocean wave resources evaluation. Renew Energy 27(3):93–97Google Scholar
  18. Rusu L, Onea F (2017) The performance of some state-of-the-art wave energy converters in locations with the worldwide highest wave power. Renew Sustain Energy Rev 75:1348–1362CrossRefGoogle Scholar
  19. Salcedo-Sanz S, Deo R, Bueno LC, Camacho-Gómez C, Ghimire S (2018) An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia. Appl Energy 209:79–94CrossRefGoogle Scholar
  20. Shen SG, Qian XZ (2003) Resources ocean—develop and utilize the rich blue treasures. Haichao PressGoogle Scholar
  21. Song LN, Liu ZL, Wang F (2015) Comparison of wind data from ERA-Interim and buoys in the Yellow and East China Seas. Chin J Oceanol Limnol 33(1):282–288CrossRefGoogle Scholar
  22. Vosough A (2011) Wave power. Intl J Multidiscipl Sci Eng 2(7):60–63Google Scholar
  23. Wan Y, Zhang J, Meng JM, Wang J (2015a) Exploitable wave energy assessment based on ERA-Interim reanalysis data—a case study in the East China Sea and the South China Sea. Acta Oceanol Sin 34(9):143–155CrossRefGoogle Scholar
  24. Wan Y, Zhang J, Meng JM, Wang J (2015b) Exploitable wave energy assessment based on ERA-Interim reanalysis data—a case study in the East China Sea and the South China Sea. Acta Oceanol Sin 34(9):143–155CrossRefGoogle Scholar
  25. Zheng CW, Li XQ (2011) Wave energy resources assessment in the China Sea during the last 22 years by using WAVEWATCH-III wave model. Period Ocean Univ Chin 41(11):5–12Google Scholar
  26. Zheng CW, Li CY (2017) Propagation characteristic and intraseasonal oscillation of the swell energy of the Indian Ocean. Appl Energy 197:342–353CrossRefGoogle Scholar
  27. Zheng CW, Li CY (2018) An overview and suggestions on the difficulty of site selection for marine new energy power plant—wave energy as a case study. J Harbin Eng Univ 39(2):200–206Google Scholar
  28. Zheng CW, Pan J (2014) Assessment of the global ocean wind energy resource. Renew Sustain Energy Rev 33:382–391CrossRefGoogle Scholar
  29. Zheng CW, Pan J, Li JX (2013a) Assessing the China Sea wind energy and wave energy resources from 1988 to 2009. Ocean Eng 65:39–48CrossRefGoogle Scholar
  30. Zheng CW, Pan J, Li JX (2013b) Assessing the China Sea wind energy and wave energy resources from 1988 to 2009. Ocean Eng 65:39–48CrossRefGoogle Scholar
  31. Zheng CW, Shao LT, Shi WL (2014) An assessment of global ocean wave energy resources over the last 45 a. Acta Oceanol Sin 33(1):92–101CrossRefGoogle Scholar
  32. Zheng CW, Gao Y, Chen X (2017) Climatic long term trend and prediction of the wind energy resource in the Gwadar Port. Acta Scientiarum Naturalium Universitatis Pekinensis 53(4):617–626Google Scholar
  33. Zheng CW, Xiao ZN, Zhou W, Chen XB, Chen X (2018a) 21st century Maritime Silk Road: a peaceful way forward. Springer, BerlinGoogle Scholar
  34. Zheng CW, Li CY, Pan J (2018b) Propagation route and speed of swell in the Indian Ocean. J Geophys Res Oceans.  https://doi.org/10.1002/2016JC012585CrossRefGoogle Scholar
  35. Zheng CW, Gao CZ, Gao Y (2019a) Climate feature and long term trend analysis of the wave energy resource of the 21st century Maritime Silk Road. Acta Energiae Solaris Sinica 40(6):1487–1493Google Scholar
  36. Zheng CW, Wu GX, Chen X, Wang Q, Gao ZS, Chen YG, Luo X (2019b) CMIP5-based wave energy projection: case studies of the South China Sea and the East China Sea. IEEE Access 7(1):82753–82763CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Chongwei Zheng
    • 1
    Email author
  • Jianjun Xu
    • 2
  • Chao Zhan
    • 3
  • Qing Wang
    • 4
  1. 1.Navigation DepartmentDalian Naval AcademyDalianChina
  2. 2.College of Ocean and MeteorologyGuangdong Ocean UniversityZhanjiangChina
  3. 3.Coastal Research InstituteLudong UniversityYantaiChina
  4. 4.Coastal Research InstituteLudong UniversityYantaiChina

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