DOI QR코드

DOI QR Code

Analysis of Wind Energy Potential on the West Coast of South Korea Using Public Data from the Korea Meteorological Administration

기상청 공공데이터를 활용한 대한민국 서해안 일대의 바람자원 분석

  • Sangkyun Kang ;
  • Sung-Ho Yu ;
  • Sina Hadadi ;
  • Dae-Won Seo ;
  • Jungkeun Oh ;
  • Jang-Ho Lee
  • 강상균 (군산대학교, 해상풍력연구원 ) ;
  • 유성호 (군산대학교, 해상풍력연구원 ) ;
  • 시나 하다디 (군산대학교, 대학원 기계공학과 ) ;
  • 서대원 (군산대학교, 조선공학과) ;
  • 오정근 (군산대학교, 조선공학과) ;
  • 이장호 (군산대학교, 기계공학부 )
  • Received : 2023.03.21
  • Accepted : 2023.07.21
  • Published : 2023.09.30

Abstract

The significance of renewable energy has been on the rise, as evidenced by the 3020 renewable energy plan and the 2050 carbon neutrality strategy, which seek to advance a low-carbon economy by implementing a power supply strategy centered around renewable energy sources. This study examines the wind resources on the west coast of South Korea and confirms the potential for wind power generation in the area. Wind speed data was collected from 22 automatic weather system stations and four light house automatic weather system stations provided by the Korea Meteorological Administration to evaluate potential sites for wind farms. Weibull distribution was used to analyze the wind data and calculate wind power density. Annual energy production and capacity factors were estimated for 15-20 MW-class large wind turbines through the height correction of observed wind speeds. These findings offer valuable information for selecting wind power generation sites, predicting economic feasibility, and determining optimal equipment capacity for future wind power generation sites in the region.

Keywords

Acknowledgement

This work was supported by KOREA HYDRO & NUCLEAR POWER CO., LTD(No. 22-Tech-06) and by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(NRF 2017R1D1A3B06032145).

References

  1. Kang, D., Ko, K, and Huh, J., 2018, "Comparative study of different methods for estimating weibull parameters: A case study on Jeju Island, South Korea", Energies, Vol. 11, No. 2, pp. 1~19. 
  2. Global Wind Energy Coundl(GWEC), 2022, Global wind report 2022. 
  3. Korea wind energy industry association, 2022, Wind power facilities in operation status 2022 edition. 
  4. Kose, R., 2004, "An evaluation of wind energy potential as a power generation source in Kiitahya, Turkey", Energy Conversion and Management, Vol. 45, No. 11-12, pp. 1631~1641. 
  5. Kang, S., Khanjari, A., You, S., and Lee, J. H., 2021, "Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea", Energy Reports, Vol. 7, pp. 7358~7373. 
  6. Mahmoodi, K., Ghassemi, H., and Razminia, A., 2020, "Wind energy potential assessment in the Persian Gulf- A spatial and temporal analysis", Ocean Engineering, Vol. 216, 107674, pp. 1~20. 
  7. Onea, F., and Rusu, E., 2022, "A spatial analysis of the offshore wind energy potential related to the Mediterranean islands", Energy Reports, Vol. 8, pp. 99~105. 
  8. Wen, Y., Kamranzad, B., and Lin, P., 2021, "Assessment of long-term offshore wind energy potential in the south and southeast coasts of China based on a 55-year datasest", Energy, Vol. 224, 120225, pp. 1~13. 
  9. Gualtieri, G., 2022, "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review", Renewable and Sustainable Energy Reviews, Vol. 167, 112741, pp. 1~20. 
  10. Oh, K Y., Kim, J. Y., Lee, J. S., and Ryu, K W., 2012, "Wind resource assessment around Korean Peninsula for feasibility study on 100MW class offshore wind farm" Renewable Energy, Vol. 42, pp. 217~226. 
  11. Kang, K. S., Oh, N. S., Ko, D. H., Jeong, S. T., and Hwang, J. D., 2018, "Assessment of offshore wind power potential for turbine installation in coastal areas of Korea", Journal of Korean Society of Coastal and Ocean Engineers, Vol. 30, No. 4, pp. 191~199. 
  12. Murthy, K.S.R., and Rahi, O.P., 2017, "A comprehensive review of wind resource assessment", Renewable and Sustainable Energy Reviews, Vol. 72, pp.1320-1342 
  13. Kang, S. K., You, S. H., Lee, J. H., Park, S. S., and Kim, H. J., 2018, "Analysis of wind resource on maldo island of kokunsangun-do, saemangeum", Journal of Wind Energy, Vol. 9, No. 4, pp. 65~71. 
  14. Korea Meteorological Administration, Open MET data portal, https://data.kma.go.kr/ 
  15. Korea Meteorological Administration, 2016, Ground meteorological observation guidelines 
  16. Korea Meteorological Administration, 2018, Meteorological climate data catalog, No. 11-136000 0-001224-02 
  17. Hwang, Y. S., Lee, W. S., Paek, I. S., Yoo, N. S., 2009, "Effectiveness of wind data from automated weather stations for wind resources prediction", Journal of Industrial Technology, Kangwon Natl. Univ., No. 29, pp. 181~186. 
  18. Azad, AK, Rasul, MG., Yusaf, T., 2014, "Statistical diagnosis of the best Weibull methods for wind power assessment for agricultural applications", Energies, Vol. 7, No. 5, pp. 3056~3085. 
  19. Ryu, K. W., Park, K. S., Lee, J. H., Oh, S. Y., Kim, J. Y., and Park, M. H., 2013, "Development of web-based wind data analysis system for hemosu-1", Journal of Wind Energy, Vol. 4, No. 1, pp. 60~67. 
  20. Justus, C.G., Hargraves, WR, Mkhail, A, Graberm, D., 1978, "Methods for estimating wind speed frequency distribution". Journal of applied meteorology, Vol. 17, pp. 350~353. 
  21. Hove, T., Madiye, L., and Musademba, D., 2014, "Mapping wind power density for Zimbabwe: A suitable weibull-parameter calculation method", Journal of Energy in Southern Africa, Vol. 25, No. 4, pp. 37~47. 
  22. Shu, Z. R., and Jesson, M., 2021, "Estimation of Weibull parameters for wind energy analysis across the UK", Journal of Renewable and Sustainable Energy, Vol. 13, No. 2, pp. 1~13. 
  23. International Electrotechnical Commission, 2017, IEC 61400-12-1, Wind energy generation systems-Part 12-1: Power performance measurements of electricity producing wind turbines 
  24. Rabbani, R., and Zeeshan, M., 2020, "Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan", Renewable Energy, Vol. 154, pp. 1240~1251. 
  25. Arenas-Lopez, J. P., and Badaoui, M, 2022, "Analysis of the offshore wind resource and its economic assessment in two zones of Mexico", Assessments, Vol. 52, 101997, pp. 1~14. 
  26. Mrsad^hi, M, Costola, D., Blocken, B., and Hensen, J. L. M., 2013, "Review of external convective heat transfer coefficient models in building energy simulation programs- Implementation and uncertainty", Applied Thermal Engineering, Vol. 56, No. 1-2, pp. 134~151. 
  27. Chavan, D. S., Gaikwad, S., Singh, A, Himanshu, Parashar, D., Saahil, V., Sankpal, J., and Karandikar, P. B., 2017, "Impact of vertical wind shear on wind turbine performance", 2017 International Conference on circuits Power and Compiling Technologies, pp. 1~6. 
  28. Gaertner, E., Rinker, J., Sethuraman, L., Anderson, B., Zahle, F., and Barter, G., 2020, "TEA Wind TCP Task 37: Definition of the IEA 15 MW offshore reference wind turbine", Technical report NREL/TP-5000-75698. 
  29. Peeringa, J., Borrd, R., Ceyhan, O., Engels, W., and Winkel, G. D., 2011, "Upwind 20MW wind turbine pre-design blade design and control", ECN-11-017 
  30. Oh, K. Y., Kim, J. Y., and Lee, J. S., 2011, "Assessment of Wind Resource Around the Korean Peninsula by Using Marine Buoys Datasets", Journal of The Korean Society for New and Renewable Energy, Vol. 7, No. 1, pp. 15~21. 
  31. Kim, J. Y., Hwang, S. J., Kim, H. G., Park, C. Y., Jeong, J. Y., 2022, "Site Adaptation of the Reanalysis Data ERA5 on the Power Prediction of Wind Farms", Journal of the Korean Solar Energy Society, Vol. 42, No. 4, pp. 79~91.