## 5 Conclusions and Future Work  
The SOS algorithm is applied to solve the parameter extraction problem of solar cell models in this paper. To validate the effectiveness of SOS, it is applied to three models including single diode model, double diode model, and PV module models. From the comparison results of SOS with five state-of-the-art algorithms, namely, ANS, BLPSO, CSO, CTLA, and LWOA, it is summarized that SOS can extract more accurate and robust values for the unknown parameters with a faster convergence rate. The superiority of SOS is also demonstrated through statistical analysis based on the [PERSON]'s rank sum test. In addition, the feasibility of SOS is further confirmed through comparison with some well-designed parameter extraction methods and it indicates that SOS is highly competitive. Meanwhile, there is still room for improvement for SOS to achieve more accurate values, especially for the double diode model. In summary, SOS behaves potential effectively in solving the parameter extraction problem of solar cell models. In future, some advanced strategies such as orthogonal learning and hybridization will be employed to further improve its performance. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**SOS Vs.** & **Single Diode Model** & **Double Diode Model** & **PV Module Model** \\ \hline ANS & \(\dagger\) (\(p=2.3044\times 10^{-8}\)) & \(\dagger\) (\(p=3.4341\times 10^{-6}\)) & \(\dagger\) (\(p=5.5646\times 10^{-12}\)) \\ BLPSO & \(\dagger\) (\(p=7.0661\times 10^{-18}\)) & \(\dagger\) (\(p=7.0661\times 10^{-18}\)) & \(\dagger\) (\(p=9.9263\times 10^{-14}\)) \\ CSO & \(\dagger\) (\(p=7.0661\times 10^{-18}\)) & \(\dagger\) (\(p=7.0661\times 10^{-18}\)) & \(\dagger\) (\(p=8.9852\times 10^{-18}\)) \\ CTLA & \(\dagger\) (\(p=2.1975\times 10^{-17}\)) & \(\dagger\) (\(p=7.5041\times 10^{-18}\)) & \(\dagger\) (\(p=9.5403\times 10^{-18}\)) \\ LWOA & \(\dagger\) (\(p=1.2866\times 10^{-17}\)) & \(\dagger\) (\(p=8.4620\times 10^{-18}\)) & \(\dagger\) (\(p=7.0661\times 10^{-18}\)) \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Statistical analysis results based on [PERSON]’s rank sum. Figure 8: Convergence curves for the PV module model. **Author Contributions:** [PERSON] developed the idea behind the present research and wrote the manuscript. [PERSON] provided theoretical analysis. [PERSON] and [PERSON] contributed to final review and manuscript corrections. [PERSON] collaborated in processing the experimental data. **Funding:** This research was funded by the National Natural Science Foundation of China (Grant No. 51867005, 51667007), the Scientific Research Foundation for the Introduction of Talent of Guizhou University (Grant No. [2017]16), the Guizhou Education Department Growth Foundation for Youth Scientific and Technological Talents (Grant No. QianJiaoHe KY Zi [2018]108), the Guizhou Province Science and Technology Innovation Talent Team Project (Grant No. [2018]5615), the Science and Technology Foundation of Guizhou Province (Grant No. [2016]1036), and the Key Science and Technology Projects of China Southern Power Grid Co., Ltd. (Grant No. GZKJQQ00000417). **Conflicts of Interest:** The authors declare no conflict of interest. **Nomenclature**