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The Transactions P of
the Korean Institute of Electrical Engineers
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Korean Journal of Air-Conditioning and Refrigeration Engineering
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2019-03
(Vol.68P No.01)
10.5370/KIEEP.2019.68.1.041
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References
1
Islama M. T., Hudaa N., Abdullahb A. B., Saidurc R., 2018, A comprehensive review of state-of- the-art concentrating solar power (CSP) technologies: Current status and research trends, Renewable and Sustainable Energy Reviews, Vol. 91, pp. 987-1018
2
Modi A., Bühler F., Andreasen J. G., Haglind F., 2017, Review of solar energy based heat and power generation systems, Renewable and Sustainable Energy Reviews, Vol. 67, pp. 1047-1064
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Lee Chang-Sung, Ji Pyeong-Shik, 2016, Modeling of Photovoltaic Power Systems using Clustering Algorithm and Modular Networks, Trans. KIEE, Vol. 65P, No. 2, pp. 108-113
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Bacher P., Madsen H., Nielsen H. A., 2009, Online short-term solar power forecasting, Solar Energy, Vol. 83, pp. 1772-1783
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Yona A., Senjyu T., Saber A. Y., Funabashi T., Sekine H., Kim C. H., 2008, Application of neural network to 24-hour-ahead generating power forecasting for PV system, IEEE Transactions on Power and Energy, Vol. 128, pp. 33-39
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Huang J., Korolkiewicz M., Agrawal M., Boland J., 2013, Forecasting solar radiation on an hourly time scale using a Coupled Auto-Regressive and Dynamical System (CARDS) model, Solar Energy, Vol. 87, pp. 136-149
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Sorkun Murat Cihan, Paoli Christophe, Incel Özlem Durmaz, 2017, Time series forecasting on solar irradiation using deep learning, International Conference on Electrical and Electronics Engineering (ELECO), pp. 151-155