Artificial neural network model of photovoltaic generator for power flow analysis in PSS registered SINCAL

This study proposes an artificial neural network (ANN) model to represent a photovoltaic generator (PVG) comprising photovoltaic panels, a boost chopper and a three-phase inverter. The main advantages of the ANN model are that it can be readily used to model a PVG of any size and type, mathematical simplicity, high accuracy with unbalanced systems and computational speed. The model was tested with the unbalanced distribution system feeder from a Canadian utility. The results show that the ANN model of a PVG is computationally fast and more accurate than simple model that ignores unbalanced three-phase terminal voltage phasors. In addition, simplicity of the proposed ANN model of PVG allows easy integration into commercial software packages such as PSS registered SINCAL as reported in this study.