Performance estimation of a thin-film photovoltaic plant based on an Artificial Neural Network model

An Artificial Neural Network (ANN) approach is used to estimate power production yield by a 1 kWp experimental micro-morph silicon modules plant located at ENEA Portici Research Centre, in Italy South region. A large dataset consisting of data, measured every five minutes and acquired from 2006 to 2012, is used for the training/test of the ANN. First, AC power production evaluation is obtained from single-hidden layer Multi-Layer Perceptron (MPL) Neural Network with two inputs consisting in ambient temperature and solar global radiation. In order to improve the approximation of the AC power, the clear sky solar radiation is then added as input of the ANN. Experimental data are reported to demonstrate the feasibility and the potentiality of the adopted solutions.

[1]  Luis Marroyo,et al.  From irradiance to output power fluctuations: the PV plant as a low pass filter , 2011 .

[2]  Giuseppe Marco Tina,et al.  Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module , 2013 .

[3]  G. Coppez,et al.  Simulation and modelling of PV-wind-battery hybrid power system , 2011, 2011 IEEE Power and Energy Society General Meeting.

[4]  L. Rajaji,et al.  Intelligent Technique Based Modeling for PVPS , 2012 .

[5]  C. Ramos-Paja,et al.  Modeling of photovoltaic fields in mismatched conditions for energy yield evaluations , 2011 .

[6]  G. Graditi,et al.  Temperature Influence on Commercial PV Optimizers Reliability , 2012 .

[7]  Soteris A. Kalogirou,et al.  Modeling and simulation of a stand-alone photovoltaic system using an adaptive artificial neural network: Proposition for a new sizing procedure , 2007 .

[8]  T. I. Maris,et al.  Modeling of a single-phase photovoltaic inverter , 2007 .

[9]  H. Kambezidis,et al.  DIFFUSE SOLAR IRRADIATION MODEL EVALUATION IN THE NORTH MEDITERRANEAN BELT AREA , 2001 .

[10]  M. Vitelli,et al.  Comparative analysis of Synchronous Rectification Boost and Diode Rectification Boost converter for DMPPT applications , 2011, 2011 IEEE International Symposium on Industrial Electronics.

[11]  Soteris A. Kalogirou,et al.  Artificial intelligence techniques for photovoltaic applications: A review , 2008 .

[12]  Giacomo Capizzi,et al.  A radial basis function neural network based approach for the electrical characteristics estimation of a photovoltaic module , 2012, ArXiv.

[13]  Gilles Notton,et al.  Calculation on an hourly basis of solar diffuse irradiations from global data for horizontal surfaces in Ajaccio , 2004 .

[14]  Massimo Vitelli,et al.  Design of dc/dc Converters for DMPPT PV Applications Based on the Concept of Energetic Efficiency , 2010 .

[15]  Salvina Gagliano,et al.  Experimental validation of a probabilistic model for estimating the double axis PV tracking energy production , 2012 .

[16]  M. Iqbal.  An introduction to solar radiation , 1983 .

[17]  Sandip Deshmukh,et al.  Modeling of hybrid renewable energy systems , 2008 .

[18]  G Graditi,et al.  Efficiency and reliability comparison of DC-DC converters for single phase grid connected photovoltaic inverters , 2010, SPEEDAM 2010.

[19]  G. Graditi,et al.  Energy performances and reliability evaluation of an optimized DMPPT boost converter , 2011, 2011 International Conference on Clean Electrical Power (ICCEP).

[20]  G. Graditi,et al.  RIAC 217Plus reliability prediction model in photovoltaic systems , 2013, 2013 International Conference on Clean Electrical Power (ICCEP).

[21]  Giuseppe Marco Tina,et al.  Analysis of forecast errors for irradiance on the horizontal plane , 2012 .

[22]  Kurt Hornik,et al.  Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.

[23]  Filippo Attivissimo,et al.  Characterization and Testing of a Tool for Photovoltaic Panel Modeling , 2011, IEEE Transactions on Instrumentation and Measurement.

[24]  Gilbert M. Masters,et al.  Renewable and Efficient Electric Power Systems , 2004 .

[25]  Gilbert M. Masters,et al.  Renewable and Efficient Electric Power Systems: Masters/Electric Power Systems , 2004 .

[26]  Nuri Gokmen,et al.  A virtual reality study of surrounding obstacles on BIPV systems for estimation of long-term performance of partially shaded PV arrays , 2013 .

[27]  S. Arul Daniel,et al.  Performance analysis of a 3 MWp grid connected solar photovoltaic power plant in India , 2013 .

[28]  Najmul Hoque,et al.  Performance of photovoltaic micro utility systems , 2013 .

[29]  Giorgio Graditi,et al.  Photovoltaic optimizer boost converters: Temperature influence and electro-thermal design , 2014 .

[30]  W. Prommee,et al.  A study of particle swarm technique for renewable energy power systems , 2010, Proceedings of the International Conference on Energy and Sustainable Development: Issues and Strategies (ESD 2010).

[31]  Giorgio Graditi,et al.  Photovoltaic power optimizers: A comparison in reliability evaluations , 2013 .