Parameter extraction of single-diode photovoltaic module using experimental current-voltage data

Accurate modeling of photovoltaic (PV) module allows proper load scheduling and avoids the uncertainties in grid. This paper uses forward-backward linear least square error (FB-LLSE) curve fitting method to estimate the parameters of PV module. The proposed method does not require any data sheet information and initial values of parameters. The proposed method utilizes the experimental data on I-V curve to extract the parameters of PV module. To validate the proposed method, three different PV modules, namely, Mono-crystalline STM6-40/36, Poly-crystalline SMP6-120/36, PWP-201, and one Real Time Clock (R.T.C.) France solar cell has been considered. The obtained results are compared with three existing methods in the literature. The performance of the proposed FB-LLSE method is studied with root mean square error (RMSE), mean absolute error (MAE), normalized root mean square error (NRMSE), and normalized mean absolute error (NMAE). The calculated with proposed FB-LLSEM is reduced by 10%, 7%, 2.26%, and 1.89%, respectively, for PWP-201, STMP-120/36, SMP6-40/36, and R.T.C France solar cell when compared to the LLSEM method available in the literature. The proposed FB-LLSE method is found to exhibit low value of RMSE for all three PV modules and one PV cell.

Automated summary

This paper proposes a new method using the forward-backward linear least square error (FB-LLSE) curve fitting method to estimate the parameters of a photovoltaic (PV) module, extracting parameters from experimental data and validating on three different modules and a solar cell, showing significant improvement in comparison to existing methods.