Parameterization of photovoltaic solar cell double-diode model based on improved arithmetic optimization algorithm

Abstract

After avoiding the Standard Test Condition (STC) related to the manufacturer of PV cells, accurate solar system modeling is considered the most important task to study this system. Several mathematical developments based-approaches or algorithms were considered valuable tools to parameterize the electrical circuit of the photovoltaic models. Thus, these parameters are well determined using optimization algorithms. To achieve this goal, an experimental database or manufacturer's datasheet is requested. This paper proposes a novel Improved Arithmetic Optimization Algorithm (IAOA) to extract the solar cell/panel parameters. Also, practical tests are presented for obtaining the measured illustration of the I-V and P-V characteristics. Thus, the Double Diode Model (DDM) of the electrical circuit of PV panel is studied considering various statistical analyzes, to know the Minimum (MinFobj,DDM), the Maximum (MaxFobj,DDM), the Average (AveFobj,DDM), and the Standard Deviation (SDFobj,DDM). The estimated I-V and P-V curves using IAOA is compared with eight other recently published algorithms. In addition, the evaluation of the proposed IAOA proves that this proposal has a satisfactory performance than all tested algorithms. The obtained results show that the IAOA is considered first in terms of effectiveness and accuracy by 9.537e−06 of standard deviation. Moreover, considering the variability of operating conditions, the proposed IAOA shows its high superiority to optimize the electrical parameters of the solar cell TDM Where it has the lowest errors by 3.623e−05 of RMSE, 4.183e−06 of MAE, and 1.397e−05 of RMSD.