**5. Conclusions**

In this study, the hybridization of whale optimization and particle swarm optimization algorithm (WOAPSO) is anticipated. The exploitation ability of PSO is only implemented in pipeline mode when WOA stops to improve the best-found solution. The collaboration of both metaheuristic algorithms can establish an effective balance between exploitation and exploration ability. The proposed technique is further used to estimate the parameter of three PV cell models, i.e., single-diode, double-diode, and SS108P PV panel module model at different operating conditions. It should be noted that this suggested technique is, for the first time, intended to track the estimation of parameters for photovoltaic models reliably. The major conclusions are classified as follows:


The proposed WOAPSO algorithm has limitation for DDM analysis. The RMSE value (9.8412 <sup>×</sup> <sup>10</sup>−<sup>4</sup> ) of WOAPSO algorithm is lower than that of recently developed metaheuristics algorithms (MLBSA, EHHO, IJAYA, and GOTLBO algorithms).

The WOAPSO is an efficient and robust technique to estimate the unknown optimized parameters of the solar PV model at different operating conditions. For future study, the implementation of proposed WOAPSO to solve the other problems related to energy optimization such as economic load dispatch, energy scheduling and optimization of PV array configuration may also be interesting for scientists and research scholars.

**Supplementary Materials:** The supplementary materials are available online at https://www.mdpi. com/2079-9292/10/3/312/s1.

**Author Contributions:** Conceptualization: A.S. (Abhishek Sharma), and A.S. (Abhinav Sharma); methodology and formal analysis: A.S. (Abhishek Sharma) and M.A.; investigation, A.S. (Abhinav Sharma); writing—original draft preparation, A.S. (Abhishek Sharma); writing—review and editing, A.S. (Abhinav Sharma), M.A. and V.J.; supervision, M.A. and B.A.; fund acquisition: B.A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported in part by the European Commission H2020 TWINNING JUMP2Excel (Joint Universal activities for Mediterranean PV integration Excellence) project under grant 810809.

**Acknowledgments:** Authors are thankful to anonymous reviewers and editor for their suggestions.

**Conflicts of Interest:** The authors declare no conflict of interest.
