Estimation of Parameters of Triple Diode Photovoltaic Models Using Hybrid Particle Swarm and Grey Wolf Optimization
Hazem Hassan Ellithy, Adel M. Taha, Hany M. Hasanien, Mahmoud A. Attia, Adel El‐Shahat, Shady H. E. Abdel Aleem
Abstract
The quality of the photovoltaic (PV) cell model impacts many simulation studies for PV systems, such as maximum power point tracking and other assessments. Moreover, due to limited information found in the datasheets of the PV cells, several parameters of the model are unavailable. Thus, this paper introduces a novel approach using a hybrid Particle Swarm and Grey Wolf Optimization algorithm to figure out these parameters under different environmental conditions. The proposed algorithm is used with two types of PV cells–Kyocera KC200GT and Canadian solar cell CS6K-280M–and can be used with any commercial type of PV module needing only parameters in the datasheet. The absolute error of the model’s simulation results is compared to the actual results collected from sites in Egypt, in an attempt to investigate the effectiveness of the suggested approach.