[1]
J.A. Duffie and W.A. Beckman, Solar engineering of thermal processes, Wiley and Sons, New York, (1991) 216–230.
Google Scholar
[2]
V. Badescu, Dynamic model of a complex system including PV cells, electric battery, electrical motor and water pump, Energy, 28 (2003) 1165–1181.
DOI: 10.1016/s0360-5442(03)00115-4
Google Scholar
[3]
N. Hamrouni, M. Jraidi and A. Chérif, Theoretical and experimental analysis of the behaviour of a photovoltaic pumping system, Solar Energy, 83 (2009) 1335–1344.
DOI: 10.1016/j.solener.2009.03.006
Google Scholar
[4]
A.M. Zaki and M.N. Eskander, Matching of photovolatic motor-pump systems for maximum efficiency operation, Renew. Energy, 7 (1996) 279–288.
DOI: 10.1016/0960-1481(95)00133-6
Google Scholar
[5]
A.N. Celik, Present status of photovoltaic energy in Turkey and life cycle techno-economic analysis of a grid-connected photovoltaic-house, Renew. Sustai. Energy Rev. 10 (2006) 370-387.
DOI: 10.1016/j.rser.2004.09.007
Google Scholar
[6]
H.M. Mashaly, A.M. Sharaf, M. Mansour and A.A. El-Sattar, A photovoltaic maximum power tracking using neural networks, in Control Applications, 1994., Proceedings of the Third IEEE Conference on, (1994) 167–172.
DOI: 10.1109/cca.1994.381232
Google Scholar
[7]
T. Hiyama, S. Kouzuma, T. Imakubo and T. Ortmeyer, Evaluation of neural network based real time maximum power tracking controller for PV system, Energy Conversion, IEEE Transactions on, 10 (1995) 543–548.
DOI: 10.1109/60.464880
Google Scholar
[8]
M. Veerachary, T. Senjyu and K. Uezato, Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller, Industrial Electronics, IEEE Transactions on, 50 (2003) 749–758.
DOI: 10.1109/tie.2003.814762
Google Scholar
[9]
E. Karatepe, M. Boztepe and M. Colak, Neural network based solar cell model, Energy Conversion Manage. 47 (2006) 1159–1178.
DOI: 10.1016/j.enconman.2005.07.007
Google Scholar
[10]
A. Karlis, T. Kottas and Y. Boutalis, A novel maximum power point tracking method for PV systems using fuzzy cognitive networks (FCN), Electric Power Syst. Res. 77 (2007) 315–327.
DOI: 10.1016/j.epsr.2006.03.008
Google Scholar
[11]
M.F. Tsai, C.S. Tseng, G.D. Hong and S.H. Lin, A novel MPPT control design for PV modules using neural network compensator, in Industrial Electronics (ISIE), 2012 IEEE International Symposium on, (2012) 1742–1747.
DOI: 10.1109/isie.2012.6237354
Google Scholar
[12]
M. Sheraz and M.A. Abido, An efficient MPPT controller using differential evolution and neural network, in IEEE Int. Conf. on Power and Energy, (2012) 378–383.
DOI: 10.1109/pecon.2012.6450241
Google Scholar
[13]
L.L. Jiang, D. Nayanasiri, D.L. Maskell and D. Vilathgamuwa, A simple and efficient hybrid maximum power point tracking method for PV systems under partially shaded condition, in Industrial Electronics Society, IECON 2013–39th Annual Conference of the IEEE, (2013).
DOI: 10.1109/iecon.2013.6699357
Google Scholar