A Database Implementation for the Study of Crystalline Silicon PV Modules Behavior

The work proposed here aims at providing scientists and decision-makers with a mean which will help in the performance modeling of PV modules. Based on one of the existing models of solar cells, we developed a behavioral database enriched by the information that can be gathered from the manufacturers' datasheets of the modules. By considering the extraction of the 5 parameters of the module as an optimization non-constraint problem at Standard Test Conditions (STC), analytical expressions without any simplification, derived from the main current-voltage equation are used. By choosing a wise initial guess value we evaluated those 5 unknows more accurately. Datasheets of 10 different types of solar modules that are installed in photovoltaic plants in Senegal were considered. Hence the methodology adopted and applied on them in the simulation process allowed us to replicate first their current-voltage and power-voltage characteristics in STC, then in changing environmental conditions. In the end, this work focused on the prediction of a twelfth part of the output power produced on the DC side before an Inverter Transformer Station (ITS) of one photovoltaic plant. The measurement values compared with the simulation results showed a good match for the same day over two years.