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2020 Vol.40, Issue 5 Preview Page

Research Article

30 October 2020. pp. 13-22
Abstract
References
1
Kleissl, J., Solar Energy Forecasting and Resource Assessment, Academic Press, 1st Ed., p. 416.
2
Diagne, M., David, M., Lauret, P., Boland, J., and Schmutz, N., Review of Solar Irradiance Forecasting Methods and a Proposition for Small-scale Insular Grids. Renewable and Sustainable Energy Reviews, Vol. 27, pp. 65-76, 2013.
10.1016/j.rser.2013.06.042
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Lee, Y.-M., Bae, J.-H., Park, J.-K., A Study on Prediction Techniques through Machine Learning of Real-time Solar Radiation in Jeju, Journal of Environmental Science International, Vol.26, No.4, pp.521-527, 2017.
10.5322/JESI.2017.26.4.521
4
Kim, C. K., Kim, H.-G., Kang, Y.-H., and Yun, C.-Y., Evaluation of UM-LDAPS Prediction Model for Daily Ahead Forecast of Solar Power Generation, Journal of the Korean Solar Energy Society, Vol. 39, pp. 71-80, 2019.
5
Korea Meteorological Administration, Evaluation of Numerical Weather Prediction System (2016), TR11- 1360709-000001-10, pp. 198, 2016.
6
Sengupta, M., Habte, A., Gueymard, C., Wilbert, S., and Renne, D., Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications (NREL/TP-5D00-68886). Golden, CO: National Renewable Energy Laboratory, 2017.
10.18777/ieashc-task46-2017-0001
7
Mathiesen, P. and Kleissl, J., Evaluation of Numerical Weather Prediction for Intra-day Solar Forecasting in the Continental United States. Solar Energy, Vol. 85, pp. 967-977, 2011.
10.1016/j.solener.2011.02.013
Information
  • Publisher :Korean Solar Energy Society
  • Publisher(Ko) :한국태양에너지학회
  • Journal Title :Journal of the Korean Solar Energy Society
  • Journal Title(Ko) :한국태양에너지학회 논문집
  • Volume : 40
  • No :5
  • Pages :13-22
  • Received Date : 2020-07-16
  • Revised Date : 2020-09-10
  • Accepted Date : 2020-09-11