Page 280 - Advances in Renewable Energies and Power Technologies
P. 280
References 253
[37] K.H. Chao, C.T. Chen, M.H. Wang, C.F. Wu, A novel fault diagnosis method based-on
modified neural networks for photovoltaic systems, advances in swarm intelligence,
Lect. Notes Comput. Sci. 6146 (2010) 531e539.
[38] S. Vergura, G. Acciani, V. Amoruso, G. Patrono, F. Vacca, Descriptive and inferential
statistics for supervising and monitoring the operation of PV plants, IEEE Trans. Ind.
Electron. 56 (2009) 4456e4464.
[39] W. Chine, A. Mellit, V. Lughi, A. Malek, G. Sulligoi, A. Massi Pavan, A novel fault
diagnosis technique for photovoltaic systems based on artificial neural networks,
Renew. Energy 90 (2016) 501e512.
[40] S. Killinger, N. Engerer, B. Mu ¨ller, QCPV: a quality control algorithm for distributed
photovoltaic array power control, Sol. Energy 143 (2017) 120e131.
[41] S. Silvestre, L. Mora-Lo ´pez, S. Kichou, F. Sa ´nchez-Pacheco, M. Dominguez-Pumar,
Remote supervision and fault detection on OPC monitored PV systems, Sol. Energy
137 (2016) 424e433.
[42] S. Silvestre, M.A. da Silva, A. Chouder, D. Guasch, E. Karatepe, New procedure for
fault detection in grid connected PV systems based on the evaluation of current and
voltage indicators, Energy Convers. Manag. 86 (2014) 241e249.
[43] S. Silvestre, S. Kichou, A. Chouder, G. Nofuentes, E. Karatepe, Analysis of current and
voltage indicators in grid connected PV (photovoltaic) systems working in faulty and
partial shading conditions, Energy 86 (2015) 42e50.
[44] S. Silvestre, Review of System Design and Sizing Tools. Practical Handbook of Photo-
voltaics: Fundamentals and Applications, Elsevier, Oxford, 2003, p. 543.
[45] C. Sah, R.N. Noyce, W. Shockley, Carrier generation and recombination in P-N junc-
tions and PeN junction characteristics, Proc IRE 45 (1957) 1228e1243.
[46] L. Castaner, S. Silvestre, Modelling Photovoltaic Systems Using PSpice, John Wiley
and Sons, 2002.
[47] J. Nelson, The Physics of Solar Cells, Imperial college press, London, 2003.
[48] E. Rodrigues, R. Melı ´cio, V. Mendes, J. Catalao, Simulation of a solar cell considering
single-diode equivalent circuit model, in: International Conference on Renewable En-
ergies and Power Quality. Spain, 13e15 April 2011, 2011.
[49] A. Dolara, S. Leva, G. Manzolini, Comparison of different physical models for PV po-
wer output prediction, Sol. Energy 119 (2015) 83e99.
[50] E. Karatepe, M. Boztepe, M. Colak, Development of a suitable model for characterizing
¸
photovoltaic arrays with shaded solar cells, Sol. Energy 81 (2007) 977e992.
[51] R.P. Kenny, E.D. Dunlop, H.A. Ossenbrink, H. Mu ¨llejans, A practical method for the
energy rating of c-Si photovoltaic modules based on standard tests, Prog. Photovolt.
Res. Appl. 14 (2006) 155e166.
[52] D.L. King, J.A. Kratochvil, W.E. Boyson, Field Experience with a New Performance
Characterization Procedure for Photovoltaic Arrays (No. SANDe98-3147C; CONF-
980735), Sandia National Labs, Albuquerque, NM (US), 1997.
[53] D.L. King, Photovoltaic module and array performance characterization methods for all
system operating conditions, in: C.E. Witt, M. Al-Jassim, J.M. Gee (Eds.), AIP Confer-
ence Proceedings, vol. 394 (1), AIP, February 1997, pp. 347e368.
[54] G.A. Rampinelli, A. Krenzinger, F.C. Romero, Mathematical models for efficiency of
inverters used in grid connected photovoltaic systems, Renew. Sustain. Energy Res.
34 (2014) 578e587.