Analytical Versus Neural Real-Time Simulation of a Photovoltaic Generator Based on a DC DC Converter

This paper presents a simulator of a photovoltaic (PV) field where the current–voltage characteristic is obtained either with a fully analytical model or with a numerical model based on a growing neural gas (GNG) network. The power stage is obtained with a dc–dc buck converter driven by the current– voltage–irradiance–temperature relation of the PV array. The improvements introduced here, with respect to previous works, are the following: 1) the mathematical model is given as a continuous surface in the irradiance domain; 2) a relation between temperature and irradiance is obtained by least square regression method; 3) the thermal constant of the PV field is introduced; and 4) an experimental prototype of higher rating has been devised and constructed. For both approaches, a more performing control technique of the converter has been used. Finally, a PV simulator prototype is experimentally tested. Some criteria for a suitable choice between the proposed approaches and the benefits obtainable by the use of the GNG are put into evidence.