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An assessment of wind energy potential at the demonstration offshore wind farm in Korea

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  • Oh, Ki-Yong
  • Kim, Ji-Young
  • Lee, Jae-Kyung
  • Ryu, Moo-Sung
  • Lee, Jun-Shin

Abstract

The construction of an offshore demonstration wind farm was planned in a southwestern sea-area of the Korean Peninsula. To estimate economic feasibility and to establish a reliable design basis, it is necessary to identify the design parameters of the demo-farm. For a reliable estimation of the design parameters, the first offshore meteorological mast, HeMOSU (Herald of the Meteorological and Oceanographic Special Research Unit), was constructed at the site of the demo-farm. In addition, supplementary meteorological masts were installed in advance at Gochang and Wangdeung-do in order to enhance the estimation of the long-term wind potential for the demo-farm. In this paper, assessments of wind energy potential are carried out with the data measured from these three meteorological masts. The analysis includes seasonal and diurnal changes in wind speed and surface roughness as well as wind/energy rose. Long-term wind potential is also estimated by using MCP (Measure-Correlate-Predict) techniques to clarify the design basis and to determine the wind turbine class in accordance with IEC 61400. The AEP (Annual Energy Production), as well as the C.F. (Capacity Factor) of the candidate site are evaluated with the estimated design parameters.

Suggested Citation

  • Oh, Ki-Yong & Kim, Ji-Young & Lee, Jae-Kyung & Ryu, Moo-Sung & Lee, Jun-Shin, 2012. "An assessment of wind energy potential at the demonstration offshore wind farm in Korea," Energy, Elsevier, vol. 46(1), pages 555-563.
  • Handle: RePEc:eee:energy:v:46:y:2012:i:1:p:555-563
    DOI: 10.1016/j.energy.2012.07.056
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    References listed on IDEAS

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    1. Lim, Hee-Chang & Jeong, Tae-Yoon, 2010. "Wind energy estimation of the Wol-Ryong coastal region," Energy, Elsevier, vol. 35(12), pages 4700-4709.
    2. Guo, Zhenhai & Zhao, Jing & Zhang, Wenyu & Wang, Jianzhou, 2011. "A corrected hybrid approach for wind speed prediction in Hexi Corridor of China," Energy, Elsevier, vol. 36(3), pages 1668-1679.
    3. Carta, José A. & Velázquez, Sergio, 2011. "A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site," Energy, Elsevier, vol. 36(5), pages 2671-2685.
    4. Islam, M.R. & Saidur, R. & Rahim, N.A., 2011. "Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function," Energy, Elsevier, vol. 36(2), pages 985-992.
    5. Onat, Nevzat & Ersoz, Sedat, 2011. "Analysis of wind climate and wind energy potential of regions in Turkey," Energy, Elsevier, vol. 36(1), pages 148-156.
    6. Ko, Kyungnam & Kim, Kyoungbo & Huh, Jongchul, 2010. "Variations of wind speed in time on Jeju Island, Korea," Energy, Elsevier, vol. 35(8), pages 3381-3387.
    7. Oh, Ki-Yong & Kim, Ji-Young & Lee, Jun-Shin & Ryu, Ki-Wahn, 2012. "Wind resource assessment around Korean Peninsula for feasibility study on 100 MW class offshore wind farm," Renewable Energy, Elsevier, vol. 42(C), pages 217-226.
    8. Rehman, Shafiqur & Ahmad, Aftab, 2004. "Assessment of wind energy potential for coastal locations of the Kingdom of Saudi Arabia," Energy, Elsevier, vol. 29(8), pages 1105-1115.
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