All Issue

2019 Vol.39, Issue 2 Preview Page

Research Article

30 April 2019. pp. 71-80
Abstract
References
1
Kleissl, J., Solar Energy Forecasting and Resource Assessment, Academic Press, 1st Ed., pp. 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
3
Lee, Y.-M., J.-H. Bae, and 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.
10.5322/JESI.2017.26.4.521
4
Korea Meteorological Administration, Evaluation of Numerical Weather Prediction System (2016), TR11-1360709-000001-10, pp. 198, 2016
5
Kim, C. K., Kim, H.-G., Kang, Y.-H., and Yun, C.-Y., Toward Improved Solar Irradiance Forecasts: Comparison of the Global Horizontal Irradiances Derived from the COMS Satellite Imagery Over the Korean Peninsula, Pure Appl. Geophys., Vol. 174, pp. 2773-2792, 2017.
10.1007/s00024-017-1578-y
6
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 : 39
  • No :2
  • Pages :71-80
  • Received Date : 2019-03-05
  • Revised Date : 2019-04-24
  • Accepted Date : 2019-04-26