[1]
W-J. Lee, Y. Liu, Y. Yang, and P. Wang, in: Forecasting power output of photovoltaic system based on weather classification and support vector machine, Industry applications society annual meeting (IAS), 2011, 1-6.
DOI: 10.1109/ias.2011.6074294
Google Scholar
[2]
C. Tao, D. Shanxu, and C. Changson, in: Forecasting power output for grid – connected photovoltaic system without using solar radiation measurement, Power electronics for distributed generation systems (PEDG), IEEE, 2010, 773-777.
DOI: 10.1109/pedg.2010.5545754
Google Scholar
[3]
A. Yona, T. Senjyu, and T. Funabashi, in: Application of recurrent neural network to short–term – ahead generating power forecasting for photovoltaic system, power engineering society general meeting, IEEE, 2007, 1-6.
DOI: 10.1109/pes.2007.386072
Google Scholar
[4]
S.A. Kalogirou, in: Applications of artificial neural networks in energy systems: a review, Energy conversion management, 40(10), 1999, 1073- 1087.
DOI: 10.1016/s0196-8904(99)00012-6
Google Scholar
[5]
H.T.C. Pedro, C.F.M. Coimbra, in: Assessment of forecasting techniques for solar power production with no exogenous inputs, Solar Energy 2012; 86(7): 2017e28.
DOI: 10.1016/j.solener.2012.04.004
Google Scholar
[6]
S. Pelland, G. Galanis and G. Kallos, in: Solar and photovoltaic forecasting through post-processing of the global environmental multiscale numerical weather prediction model, Progress in Photovoltaics: Research and Applications 2013; 21(3): 284e96.
DOI: 10.1002/pip.1180
Google Scholar
[7]
P. Bacher, H. Madsen and H.A. Nielsen, in: Online short-term solar power forecasting, Solar Energy 2009; 83(10): 1772e83.
DOI: 10.1016/j.solener.2009.05.016
Google Scholar
[8]
P. Mandal, S. Madhira, A.U. Haque, J. Meng and R.L. Pineda, in: Forecasting power output of solar photovoltaic system using wavelet transform and artificial intelligence techniques, Procedia Computer Science 2012; 12: 332e7.
DOI: 10.1016/j.procs.2012.09.080
Google Scholar
[9]
S.K. Chow, E.W. Lee and D.H. Li, in: Short-term prediction of photovoltaic energy generation by intelligent approach, Energy and Buildings 2012; 55: 660e7.
DOI: 10.1016/j.enbuild.2012.08.011
Google Scholar
[10]
E. Lorenz, T. Scheidsteger, J. Hurka, D. Heinemann and C. Kurz, in: Regional PV power prediction for improved grid integration, Progress in Photovoltaics: Research and Applications 2011; 19(7): 757e71.
DOI: 10.1002/pip.1033
Google Scholar
[11]
A. Yona, T. Senjyu, T. Funabashi and C-H. Kim, in: Determination method of insolation prediction with fuzzy and applying neural network for long-term ahead PV power output correction, IEEE Transactions on Sustainable Energy 2013; 4(2): 527e33.
DOI: 10.1109/tste.2013.2246591
Google Scholar
[12]
S. Jafarzadeh, M. Fadali and C. Evrenosoglu, in: Solar power prediction using interval type-2 TSK modeling, IEEE Transactions on Sustainable Energy 2013; 4(2): 333e9.
DOI: 10.1109/tste.2012.2224893
Google Scholar
[13]
G. Capizzi, F. Bonanno, in: A Wavelet Based Prediction of Wind and Solar Energy for Long-Term Simulation of Integrated Generation Systems, Proceedings of the 2010 International Conference on Modeling, Identification and Control, Okayama, Japan, July, (2010).
DOI: 10.1109/speedam.2010.5542259
Google Scholar
[14]
K. Mitsuru, T. Akira and N. Yousuke, in: Forecasting Electric Power Generation in a Photovoltaic Power System for an Energy Network, IEEE Transactions on Power and Energy, Volume 127, Issue7, pp.847-853(2007).
DOI: 10.1541/ieejpes.127.847
Google Scholar
[15]
A. Chaouachi, R. M. Kamel, R. Ichikawa, H. Hayashi and K. Nagasaka, in: Neural network ensemble-based solar power generation short-term forecasting, World Acad. Sci., Eng. Technol. 54 (2009), p.54–59.
Google Scholar
[16]
Y-Z. Li, J-C. Niu, in: Forecast of power generation for grid-connected photovoltaic system based on grey model and Markov chain, 2008 3rd IEEE Conference on Industrial Electronics and Applications, pp.1729-1733, June (2008).
DOI: 10.1109/iciea.2008.4582816
Google Scholar
[17]
Y-Z. Li, J-C. Niu, in: Forecast of power generation for grid-connected photovoltaic system based on Markov chain, IEEE Asia-Pacific Power and Energy Engineering Conference, vol1, pp.652-655, (2009).
DOI: 10.1109/appeec.2009.4918386
Google Scholar
[18]
Y-Z. Li, J-C. Niu, in: Short-Term Forecast of Power Generation for Grid-Connected Photovoltaic System Based on Advanced Grey-Markov Chain, Energy and Environment Technology, 2009 International Conference, Oct. 2009. pp: 275-278.
DOI: 10.1109/iceet.2009.305
Google Scholar