An accurate parameter estimation approach to modeling of solar photovoltaic module using hybrid grey wolf optimization

This paper proposes a hybrid method for an accurate parameter estimation of the solar photovoltaic (PV) module. The proposed method combines the features of analytical as well as the optimization technique to ensure the speed and accuracy in computation. Two-diode model consist of seven unknown parameters namely the photocurrent (IPV$$ {I}_{\mathrm{PV}} $$), reverse saturation current of diode D1$$ {D}_1 $$ and D2$$ {D}_2 $$ (I01$$ {I}_{01} $$ and I02$$ {I}_{02} $$), series resistance (Rs$$ {R}_s $$), shunt resistance (Rsh$$ {R}_{\mathrm{sh}} $$), diode ideality factor for diode D1$$ {D}_1 $$ and D2$$ {D}_2 $$ (A1$$ {A}_1 $$ and A2$$ {A}_2 $$). First five parameters are analytically determined with the help of area under the curve, while the remaining two are optimally calculated by using the Grey Wolf Optimization technique. The results obtained by simulation are verified with the experimental data of different PV module and the error is calculated. The superiority of the proposed estimation approach is compared with the recent literature and the results are presented. The proposed model is very useful for the solar PV module designers and simulators to realize its physical characteristics.