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동심원 등가풍속을 이용한 대기안정도에 따른 풍력자원 변화에 관한 연구

Accounting for the Atmospheric Stability in Wind Resource Variations and Its Impacts on the Power Generation by Concentric Equivalent Wind Speed

  • 류건화 (부산대학교 대기과학과) ;
  • 김동혁 (부산대학교 환경연구원) ;
  • 이화운 (부산대학교 대기과학과) ;
  • 박순영 (부산대학교 환경연구원) ;
  • 유정우 (부산대학교 대기과학과) ;
  • 김현구 (한국에너지기술연구원 신재생에너지 지원센터)
  • Ryu, Geon-Hwa (Div. of Earth Environmental System, Pusan National University) ;
  • Kim, Dong-Hyeok (Institute of Environment Studies, Pusan National University) ;
  • Lee, Hwa-Woon (Div. of Earth Environmental System, Pusan National University) ;
  • Park, Soon-Young (Institute of Environment Studies, Pusan National University) ;
  • Yoo, Jung-Woo (Div. of Earth Environmental System, Pusan National University) ;
  • Kim, Hyun-Goo (Korea Institute of Energy Research)
  • 투고 : 2016.01.11
  • 심사 : 2016.02.26
  • 발행 : 2016.02.28

초록

The power production using hub height wind speed tends to be overestimated than actual power production. It is because the hub height wind speed cannot represent vertical wind shear and blade tip loss that aerodynamics characteristic on the wind turbine. The commercial CFD model WindSim is used to compare and analyze each power production. A classification of atmospheric stability is accomplished by Monin-Obukhov length. The concentric wind speed constantly represents low value than horizontal equivalent wind speed or hub height wind speed, and also relevant to power production. The difference between hub height wind speed and concentric equivalent wind speed is higher in nighttime than daytime. Under the strongly convective state, power production is lower than under the stable state, especially using the concentric equivalent wind speed. Using the concentric equivalent wind speed considering vertical wind shear and blade tip loss is well estimated to decide suitable area for constructing wind farm.

키워드

참고문헌

  1. Oh, M. J., Variability Estimation of Wind Power Fluctuation in South Korea Based on Electricity Supply and Demand Plan, M. Dissertation, Hongik University, 2014.
  2. Wagner R., Courtney M., Gottschall J., Lindelow-Marsden P., Accounting for the speed shear in wind turbine power performance measurement, 14(8), pp. 993-1004, 2011. https://doi.org/10.1002/we.509
  3. Dennis L. Elliot and Jack B. Cadogan, Effects of wind shear and turbulence on wind turbine power curves, European Community Wind Energy, 1990.
  4. Antoniou I., Wagner R., Soren M. Pedersen, Uwe Paulsen, Helge A. Madsen, Hans E. Jorgensen, Kenneth Thomsen, Peder Enevoldsen, Leo Thesbjerg, Influence of wind characteristics on turbine performance, European Wind Energy Conference and Exhibition (EWEA), 2007.
  5. Wagner R., Canadillas B., Clifton A., Feeney S., Nygaard N., Poodt M., Martin C., Tuxen E., Wagenaar J., Rotor equivalent wind speed for power curve measurement comparative exercise for IEA Wind Annex 32, Journal of Physics : Conference Series. 524, 012108, 2014. https://doi.org/10.1088/1742-6596/524/1/012108
  6. McCosker J., Design and Optimization of a Small Wind Turbine, M. Dissertation, Rensselaer Polytechnic Institute, 2012.
  7. Yoo, J. W., Lee, H. W., Lee, S. H., Kim, D. H., Characteristics of Vertical Variation of Wind Resources in Planetary Boundary Layer in Coastal Area using Tall Tower Observation, Journal of Korean Society for Atmospheric Environment, Vol. 28, No. 6, pp. 633-638, 2012.
  8. Antoniou I. and Soren M. Pedersen, Influence of turbulence, wind shear and low-level jets on the power curve and the AEP of a wind turbine, European Wind Energy, 2009.
  9. Wharton S. and Lundquist K. L., Assessing atmospheric stability and the impacts on wind characteristics at an onshore wind farm, Wind Energy, Vol. 15, Issue 4, pp. 525-546, 2012. https://doi.org/10.1002/we.483
  10. Wharton S. and Lundquist K. L., Atmospheric stability affects wind turbine power collection, Environ. Res. Lett. 7, pp. 2-8, 2012.
  11. Rareshide E, Tindal A, Johnson C, Graves AM, Simpson E, Bleeg J, Harris T, Schoborg D, Effects of complex wind regimes on turbine performance. In : Scientific proceedings, American Wind Energy Association WINDPOWER Conference, Chicago, ILL (USA), 2009.
  12. Hunter R, Pedersen TF., Dunbabin P., Antoniou A., Frandsen S., Klug H., Albers A., Lee, W. K., European wind turbines testing procedure developments. Task 1 : Measurement method to verify wind turbine performance characteristics", Riso National Laboratory, Roskilde, RISOE R-1209 (EN), 2001.
  13. Honrubia A., Vigueras-Rodriquez A., Gomez E., Lazaro, D. Rodriguez-Sanchez, The Influence of Wind Shear in Wind Turbine Power Estimation, 2010.
  14. Sumner J. and Masson C., Influence of atmospheric stability on wind turbine power performance curves, Journal of Solar Energy Engineering, Vol. 128, pp. 531-538, 2006. https://doi.org/10.1115/1.2347714
  15. Rienecker M. R., and Co-authors, MERRA: NASA's Modern-Era Retrospective Analysis for Research and Applications, Journal of Climate, Vol. 24, Issue 14, 2011.
  16. Lileo S., Berge E,, Undheim O., Klinkert R., Bredesen R., Vindteknikk K., Long-term correction of wind measurements, State of the are, guidelines and future work, Elforsk report 13:18, 2013.
  17. MEASNET, Evaluation of Site-Specific Wind Conditions Version 1, pp. 8-12, 2009.
  18. Woo, J. K., Kim, H. G., Paek, I. S., Yoo, N. S., Nam, Y. S., Wind Speed Prediction in Complex Terrain using a Commercial CFD Code, Journal of the Korean Solar Energy Society, Vol. 31, Issue 6, pp. 8-22, 2011. https://doi.org/10.7836/kses.2011.31.6.008
  19. Kim. Jin-Han, Il-Han Kwon., Ung-Sik Park., Neung-Soo Yoo., In-Su Paek., "Prediction of Annual Energy Production of Wind Farms in Complex Terrain using MERRA Reanalysis Data", Journal of the Korean Solar Energy Society, Vol. 34, No. 2, pp.82-90, 2014.
  20. Tristan Wallbank, WindSim Validation Study -CFD validation in Complex terrain, pp. 1-7, 2008.
  21. Park, K. S., Prediction of Annual Energy Production for Wind Farm using Computational Fluid Dynamics and Various Wake Models, M. Dissertation, Dept. of Aerospace Engineering, Chonbuk National University, 2015.
  22. Hwang, J. W., You, K. P., Kim, H. Y., Comparison of Wind Energy Density Distribution Using Meteorological Data and Weibull Parameters, Journal of the Korean Solar Energy Society, Vol. 30, No. 2, pp. 54-64, 2010.
  23. Schubel P. J., Crossley R. J., Wind Turbine Blade Design, Energies, Vol. 5, No.9, pp. 3425-3449, 2012. https://doi.org/10.3390/en5093425
  24. Wharton S. and Lundquist K. L., Atmospheric Stability Impacts on Power Curves of Tall Wind Turbines - An Analysis of a West Coast North American Wind Farm, Environ. Res. Lett 7, 2010.
  25. Monin A. S. and Obukhov A. M., Basic laws of turbulent mixing in the ground layer of the atmosphere, Tr. Akad. Nauk SSSR Geoph. Inst. 151: 163-187, 1954.
  26. Venora A., Monin-Obukhov Similarity Theory Applied to Offshore Wind Data_Validation of Models to Estimate the Offshore Wind Speed Profile in the North Sea, Master of Science Thesis, Delft, 5th, 2009.
  27. Ko, J. W., Lee, B. G., An Accuracy Estimation of AEP Based on Geographic Characteristics and Atmospheric Variations in Northern East Region of Jeju Island, The Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 30, No. 3, pp. 295-303, 2012. https://doi.org/10.7848/ksgpc.2012.30.3.295
  28. Jeong, S. Y., Study on the offshore Construction and Operation Characteristic of Large Scale Wind Turbines in the Domestic Typhoon Condition, M. Dissertation, Hoseo University, 2015.