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Assessment of offshore wind energy at Younggwang in Korea

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  • Lee, Myung Eun
  • Kim, Gunwoo
  • Jeong, Shin-Taek
  • Ko, Dong Hui
  • Kang, Keum Seok

Abstract

This study aimed to assess the potential of offshore wind power generation at Younggwang in Korea which is candidate site of the offshore wind farm planned to be constructed till 2019. Toward this purpose, offshore meteorological tower called HEMOSU-1 was installed and has collected the wind and other meteorological data since October, 2010. The Weibull model was fitted to the frequency distribution of data and it was found that the measured data fit well to Weibull models with properly estimated parameters. Winter was found to be the best for harnessing wind energy because of the high wind speeds and consistent wind direction from the northwestern Siberian high. An assessment of the available power density at the height of 97.35m indicates that there is an abundant wind power density—averaged to be 429.20W/m2 annually and 509.97W/m2 during winter. After testing various commercial wind turbines with rated power in the range of 3–7MW, REpower 5M was chosen for the analysis of installation at the wind farm in Younggwang. It was found that the annual energy production is expected to be about 7096GWh/yr.

Suggested Citation

  • Lee, Myung Eun & Kim, Gunwoo & Jeong, Shin-Taek & Ko, Dong Hui & Kang, Keum Seok, 2013. "Assessment of offshore wind energy at Younggwang in Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 131-141.
    • Handle: RePEc:eee:rensus:v:21:y:2013:i:c:p:131-141
    DOI: 10.1016/j.rser.2012.12.059
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    14. Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    15. Colak, Ilhami & Fulli, Gianluca & Bayhan, Sertac & Chondrogiannis, Stamatios & Demirbas, Sevki, 2015. "Critical aspects of wind energy systems in smart grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 155-171.
    16. Ali, Sajid & Lee, Sang-Moon & Jang, Choon-Man, 2018. "Statistical analysis of wind characteristics using Weibull and Rayleigh distributions in Deokjeok-do Island – Incheon, South Korea," Renewable Energy, Elsevier, vol. 123(C), pages 652-663.
    17. Shih-Chieh Liao & Shih-Chieh Chang & Tsung-Chi Cheng, 2021. "Managing the Volatility Risk of Renewable Energy: Index Insurance for Offshore Wind Farms in Taiwan," Sustainability, MDPI, vol. 13(16), pages 1-27, August.
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    19. Shu, Z.R. & Li, Q.S. & He, Y.C. & Chan, P.W., 2016. "Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications," Applied Energy, Elsevier, vol. 169(C), pages 150-163.

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