- Volume 19 Issue 8
Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.
Wind power;Wind profiler;Variational data assimilation
- 기상연구소, 2003, 한반도 악기상 집중 관측 사업(III) 3, 25-45.
- 방형준, 2007, 풍력발전기술의 현황과 전망, 한국태양에너지학회, 6(2), 3-12.
- 에너지관리공단 신.재생에너지센터, 2009, 신.재생에너지 보급통계(2009년 판), 14-15.
- 풍력발전연구센터, 2009, 국가바람지도, http://www. kier-wind.org/sub24.html.
- Alexandre, C., Crespo, A., Navarro, J., Lizcano, G., Madsen, H., Feitosa, E., 2008, A review on the young history of the wind power short-term prediction, Renewable and Sustainable Energy Reviews, 12, 1725-1744. https://doi.org/10.1016/j.rser.2007.01.015
- Barker, D. M., Huang, W., Guo, Y. R., Bourgeois, A., Xiao, X. N., 2004, A Three-Dimensional Variational Data Assimilation System for MM5: Implementation and Initial Results, Mon. Wea. Rev., 132, 897-914. https://doi.org/10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2
- Elliott, D. L., Holladay, C. G., Barchet, W. R., Foote, H. P., Sansusky, W. F., 1986, Wind Energy Resource Atlas of the United States, Pacific Northwest Laboratory, U. S. Department of Energy.
- EMD(Energi-og Miljodata), 2001, The Danish Wind Resource Map with Data Export to GIS-Format, http://www.emd.dk/
- Emilio, M., Crespo, A., Jimenez, A., Garcia, J., Manuel, F., 2007, Wind energy resource assessment in Madrid region, Renewable Energy, 32, 1467-1483. https://doi.org/10.1016/j.renene.2006.06.015
- Ide, K., Courtier, P., Ghil, M., Lorenc, A. C., 1997, Unified notation for data assimilation: Operational, sequential and variational, J. Met. Soc. Japan, 75, 181-189. https://doi.org/10.2151/jmsj1965.75.1B_181
- Kariniotakis, G., Mayer, D., Moussafir, J., Chevallaz- Perrier, R., Usaola, J., Sachez, I., 2003, ANEMOS: development of a next generation wind power forecasting system for the large-scale integration of onshore & offshore wind farms. In Proceedings of European wind energy conference, Madrid.
- Kim, Y. C., Chung, C., Lee, E. C., Chun, Ch-H., Han, K. S., Kim, Y. W., 2006, Analysis of wind resources of the South seashore of Jeonnam province, Proceedings of the Korean Soc. for New and Renewable Energy, Autumn, 281-285.
- Kim H. G., Jang, M. S., Kyong, N. Ho., Lee, H. W., Choi, H. J., Kim, D. H., 2006a, Establishment of the low-resolution national wind map by numerical wind simulation, J. of the Korean Solar Energy Soc., 26(4), 31-38.
- Kim, H. G., Lee, Y. S., Jang, M. S., Kyong, N. H., 2006b, A study on development of a forecasting model of wind power generation for Walryong site, J. of the Korean Solar Energy Soc., 26(2), 27-34.
- Kim, H. G., Lee, Y. S., Jang, M. S., Kyong, N. H., 2006c, Development of the wind power forecasting system, KIER forecaster, J. of The Korean Soc. for New and Renewable Energy, 2(2), 37-43.
- Ko, K. N., Kim, K. B., Huh, J. C., 2008, Characteristics of wind for long-term period (10 years) at Seoguang site on Jeju iland, Journal of the Korean Solar Energy Society, 28(3), 45-52.
- Lee, H. W., Kim, M. J., Kim, D. H., Kim, H. G., Lee, S. H., 2009a, Investigation of the assimilated surface wind characteristics for the evaluation of wind resources, Korean J. of Atmos. Environ, 25(1), 1-14. https://doi.org/10.5572/KOSAE.2009.25.1.001
- Lee, H. W., Park, S. Y., Lee, S. H., Lim, H. H., 2009b, Characteristics of ozone advection in vertical observation analysis around complex coastal area, Korean J. of Atmos. Environ, 25(1), 57-74. https://doi.org/10.5572/KOSAE.2009.25.1.057
- Lee, S. H., Lee, H. W., Kim, D. H., Kim, H. G., 2007, Analysis of the relation between spatial resolution of initial data and satellite data assimilation for the evaluation of wind resources in the Korean Peninsula, Korean J. of Atmos. Environ, 23(6), 653-665. https://doi.org/10.5572/KOSAE.2007.23.6.653
- Manwell, J. F., Rogers, A. L., McGowan, J. G., Bailey, B. H., 2002, An offshore wind resource assessment study for New England, Renewable Energy, 27, 175-187. https://doi.org/10.1016/S0960-1481(01)00183-5
- Michael, K., 2002, A new wind zone map of Germany, Journal of Wind Engineering and Industrial Aerodynamics, 90, 1271-1287. https://doi.org/10.1016/S0167-6105(02)00257-X
- Mike, F., 2001, Assimilation technique (3): 3dvar, ECMWF, Meteorological Training Course Lecture Series.
- NCAR, 2008, A description of the advanced Research WRF version 3.
- Park, O. R., Kim, Y. S., Cho, C. H., 2005, The Observing System Experiments with the Windprofiler and Autosonde at Haenam, Asia-Pacific Journal of Atmospheric Sciences, 41(1), 57-71.
- Parrish, D. F., Derber, J. C., 1992, The National Meteorological Center's Spectral Statistical Interpolation analysis system, Mon. Wea. Rev., 120, 1747-1763. https://doi.org/10.1175/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2
- Rehman, S., El-Amin, I. M., Ahmad, F., Shaahid, S. M., Al-Shehri, A. M., Bakhashwain, J. M., 2007, Wind power resource assessment for Rafha, Saudi Arabia, Renewable and Sustainable Energy Reviews, 11, 937-950. https://doi.org/10.1016/j.rser.2005.07.003
- Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X. Y., Wang, W., Powers, J. G., 2008, A description of the advanced research WRF version 3, NCAR Technical Note, NCAR/TN-475+STR.
- Skjold, R. N., 1996, Wind Energy Planning in Denmark, WREC 1996.
- Benjamin, S. G., Schwartz, B. E., Szoke, E. J., Koch, S. E., 2004, The value of wind profiler data in U.S. weather forecasting, Bull. Amer. Meteor. Soc., 85, 1871-1886. https://doi.org/10.1175/BAMS-85-12-1871
- UCAR, 2001, Understanding Data Assimilation: How Models Create Their Initial Conditions, www.meted. ucar.edu.
연구 과제 주관 기관 : 에너지기술연구원