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A Feasibility Study on Annual Energy Production of the Offshore Wind Farm using MERRA Reanalysis Data

해상풍력발전단지 연간발전량 예측을 위한 MERRA 재해석 데이터 적용 타당성 연구

  • Song, Yuan (Dept. of Convergence System Engineering, Kangwon National University) ;
  • Kim, Hyungyu (Dept. of Convergence System Engineering, Kangwon National University) ;
  • Byeon, Junho (Dept. of Convergence System Engineering, Kangwon National University) ;
  • Paek, Insu (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University) ;
  • Yoo, Neungsoo (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University)
  • 송원 (강원대학교 융합시스템공학과) ;
  • 김현규 (강원대학교 융합시스템공학과) ;
  • 변준호 (강원대학교 융합시스템공학과) ;
  • 백인수 (강원대학교 기계메카트로닉스공학과) ;
  • 유능수 (강원대학교 기계메카트로닉스공학과)
  • Received : 2015.02.25
  • Accepted : 2015.04.14
  • Published : 2015.04.30

Abstract

A feasibility study to estimate annual energy production of an offshore wind farm was performed using MERRA reanalysis data. Two well known commercial codes commonly used to wind farm design and power prediction were used. Three years of MERRA data were used to predict annual energy predictions of the offshore wind farm close to Copenhagen from 2011 to 2013. The availability of the wind farm was calculated from the power output data available online. It was found from the study that the MERRA reanalysis data with commercial codes could be used to fairly accurately predict the annual energy production from offshore wind farms when a meteorological mast is not available.

Keywords

References

  1. Roland Berger, Offshore Wind Toward 2020-On the Pathway To Cost Competitiveness, Roland Berger Strategy Consultants, 2013
  2. Offshore Wind Farm Council, the Southwest 2.5GW offshore wind energy synthesis promotion plan, Ministry of Knowledge Economy, 2011
  3. Schwartz, M., George, R., & Elliott, D. The Use of Reanalysis Data for Wind Resource Assessment at the National Renewable Energy Laboratory. In EWEC-CONFERENCE, pp. 1093-1096, 1999
  4. Kim, B. M., Woo, J. K., Kim, H. G., Paek, I. S., & Yoo, N. S. Validation Study of the NCAR Reanalysis Data for a Offshore Wind Energy Prediction. Journal of the Korean Solar Energy Society, Vol. 32, No. 1, pp. 1-7. 2012 https://doi.org/10.7836/kses.2012.32.1.001
  5. Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., ... & Woollen, J., MERRA: NASA's Modern-era Retrospective analysis for Research and Applications. Journal of Climate, Vol. 24, No.14, pp. 3624-3648, 2011 https://doi.org/10.1175/JCLI-D-11-00015.1
  6. Jimenez, B., Monnich, K., & Durante, F. Comparison between NCEP/NCAR and MERRA Reanalysis Data for Long Term Correction in Wind Energy Assessment. The European Wind Energy Association, 2012
  7. LORC Knowledge, http://www.lorc.dk/ offshore-windfarms-map/middelgrunden, 2014
  8. U.S. Geological Survey, http://srtm.usgs.gov/, 2014
  9. WAsP,DTU Wind Energy, Riso Campus, Denmark, http://www.wasp.dk/Support-and-services/FAQ, 2014
  10. Global Modeling and Assimilation Office Earth Sciences Division, GAO Office Note No. 1(Version 2.3), 2012
  11. MEASNET Organisation, Evaluation of Site-Specific Wind Conditions Version 1, pp.11-13, 2009
  12. Riso National Laboratory, Roskilde, Denmark, European Wind Atlas, The Commission of the European Communities Directorate-General for Science, Research and Development, 1989
  13. EMD, WindPRO Ver 2.8 Manual, http://www.emd.dk, 2013
  14. Middelgrundens Vindmollelaug I/S, http://www.middelgrund.dk, 2014

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