**4. Results and Discussion**

/<sup>ଶ</sup> ℃ In this section, we examine the validity of the STO algorithm and describe how we tested it under standard temperature conditions (1000 W/m<sup>2</sup> at 25 ◦C) utilizing primarily one R.T.C France solar cell and polycrystalline PV module (SS2018P). The extracted PV module characteristics were tracked and employed to generate simulated I-V and P-V data sets. The dependability of the STO algorithm was examined and compared to four metaheuristic algorithms: GSA [41], SCA [42], GWO [43], and WOA [44]. The size of the sample and the objective function evaluations for the experiment were fixed to 30 and 50,000, respectively. In addition, at least 30 independent runs were performed to avoid duplication.

The effectiveness of the proposed method was evaluated using several empirical constraints, e.g., internal absolute error (IAE), correctness of the curve-fitting, and global minimum convergence rates. The current and voltage data for the R.T.C France solar cell [45] and the SS2018P polycrystalline PV module [38] were collected experimentally. In the SS2018P PV module, 36 polycrystalline cells were connected serially [38]. Table 1 tabulates the exploration ranges for every parameter (i.e., upper and lower bounds). These ranges were utilized by investigators in this study. The STO algorithm [46] was simulated on a MATLAB 2018a (MathWorks, Mexico, DF, Mexico) platform with an Intel ® core TM i5-HQ CPU running at turbo frequency of 4.8 GHz and 8 GB of RAM.


**Table 1.** The parameter range for SDM of a solar cell and a PV module.
