International Journal of Ocean System Engineering

  • 제3권4호
  • /
  • Pages.209-217
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  • 2013
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  • 2233-6478(pISSN)
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  • 2233-7059(eISSN)
한국해양공학회 (Korean Society of Ocean Engineers)
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Study on Mooring System Design of Floating Offshore Wind Turbine in Jeju Offshore Area

  • Kim, Hyungjun (Department of Naval Architecture and Ocean Engineering, Inha University) ;
  • Jeon, Gi-Young (Department of Naval Architecture and Ocean Engineering, Inha University) ;
  • Choung, Joonmo (Department of Naval Architecture and Ocean Engineering, Inha University) ;
  • Yoon, Sung-Won (Department of Naval Architecture and Ocean Engineering, Inha University)
  • 투고 : 2013.09.27
  • 심사 : 2013.11.29
  • 발행 : 2013.11.30
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초록

This paper presents a mooring design procedure for a floating offshore wind turbine. Offshore environmental data for Jeju are taken from KHOA (Korea Hydrographic and Oceanographic Administration) and used for the environmental conditions in numerical analyses. A semi-submersible-type floating wind system with a 5-MW-class wind turbine studied by the DeepCwind Consortium is applied. Catenary mooring with a studless chain is chosen as the mooring system. Design deliverables such as the nominal sizes of chain and length of the mooring line are decided by considering the long-term prediction of the breaking strength of the mooring lines where a 100-year return period is used. The designed mooring system is verified using a fatigue calculation based on rain-flow cycle counting, an S-N curve, and a Miner's damage summation of rule. The mooring tension process is obtained from time-domain motion analyses using ANSYS/AQWA.

키워드

참고문헌

  1. Ansys (2010a). AQWA User's Manual Version 13.0, USA.
  2. Ansys (2010b). AQWA Reference Manual Version 13.0, USA.
  3. ASTM, 2005. Standard Practice for Cycle Counting in Fatigue Analysis. E 1049-85(Reapproved 2005), ASTM International, USA.
  4. Brommundt, M., Krause, L., Merz, K., Musku-lus, M., (2012). Mooring system optimization for floating wind turbines using frequency domain analysis, Energy Procedia 24 ; 289-296. https://doi.org/10.1016/j.egypro.2012.06.111
  5. Det Norske Veritas(DNV) (2010a). Offshore Standard DNV_OS_E301, Position Mooring. DNV, Norway.
  6. Det Norske Veritas (DNV) (2010b). Recommended Practice DNV_RP_C205, Environmental Conditions and Environmental Loads. DNV, Norway.
  7. Frank M. White (2008). Fluid Mechanics, 6th Edition, McGraw-Hill, New York.
  8. Jung, D.H., Nam, B.W., Shin, S.H., Kim, H.J., Lee, H.S., Moon, D.S., Song, J.H., (2012). Investigation of Safety and Design of Mooring Lines for Floating Wave Energy Conversion, Journal of Ocean Engineering and Technology Vol. 26-4: 77-85. https://doi.org/10.5574/KSOE.2012.26.4.077
  9. J. Jonkman, S. Butterfield, W. Musial and G. Scott (2009). Definition of a 5-MW Reference Wind Turbine for Offshore System Development, NREL/TP-500-38060, Renewable Energy Laboratory, Colorado, USA.
  10. Maruo, H., 1960. The Drift of a Body Floating in Waves. Journal of Ship Research, 4(3), USA.
  11. Shin, H.K., Kim, K.M., (2011). Motion Analysis of 5-MW Floating Offshore Wind Turbine, Journal of Ocean Engineering and Technology, 25(5): 64-68. https://doi.org/10.5574/KSOE.2011.25.5.064
  12. Shin, H.K., (2011). Model Test of the OC3-Hywind Floating Offshore Wind Turbine, International Offshore and Polar Engineering Conference, Maui, Hawaii, USA.
  13. Shin, H.K., (2013). OC4 Semi-Submersible Offshore wind turbine model test & simulation by UOU-FAST, Annual spring meeting, KAOSTS-SNAK, Jeju.
  14. Xiaohong C., Jun Z., Wei M., (2001). On dynamic coupling effects between a spar and its mooring lines, Ocean Engineering, Vol. 28: 863-887. https://doi.org/10.1016/S0029-8018(00)00026-3
  15. Yu M., Zhiqiang H., (2013). Dynamic analysis for a spar-type wind turbine under different sea states, International Conference on Ocean, Off-shore and Arctic Engineering, Nantes, France.

피인용 문헌

  1. Fatigue damage analysis for a floating offshore wind turbine mooring line using the artificial neural network approach vol.12, pp.sup1, 2017, https://doi.org/10.1080/17445302.2016.1254522