**4. Results and Discussion**

We analyzed the feasibility of the TSA algorithm and evaluated it using mainly one polycrystalline PV module (Photowatt-PWP201) under standard temperature conditions (i.e., 1000 W/m<sup>2</sup> at 30 ◦C). As a result, the retrieved PV module parameters were monitored and used to create simulated I-V data. The reliability of the WOAPSO is evaluated and compared with six metaheuristics algorithms, i.e., GSA [7], SCA [8], GWO [9], PSO [10], WOA [11], PSOGSA [12], as well as other algorithms existing in the literature. For the experiment, the sample size and the objective function evaluations are set between 30 and 50,000, respectively. Furthermore, a minimum of 30 separate runs are carried out to prevent contingency.

The efficiency of the proposed method is evaluated based on distinct empirical tools such as the internal absolute error (IAE), the Relative Error (RE), the precision of the curve fitting, and the global minimum convergence patterns. The experimental values of current and voltage are taken from [13] by using Photowatt-PWP201 (Photowatt, Bourgoin-Jallieu, France). The Photowatt-PWP201 PV module is composed of 36 polycrystalline cells arranged in a series to generate current-voltage data under standard temperature conditions. The data collection consists of a total of 23 for the PV module. For a reasonable comparison, the search ranges (i.e., upper and lower bound) for each parameter are tabulated in Table 1, which are the same as those being used by investigators in [13–15]. The TSA algorithm is implemented on the MATLAB 2018a (MathWorks, Mexico) platform with Intel ® core ™ i7-HQ CPU, 2.4 GHz, 16 GB RAM laptop.


**Table 1.** Range of parameters for solar photovoltaic (PV) module.
