**5. Conclusions**

In response to the issues of low tracking accuracy and susceptibility to local optima in classical PSO algorithms, as well as the problems of slow convergence speed and large oscillation in the BOA, this study introduces a novel PSO-BOA algorithm based on the PSO and BOA. The paper simulated four different scenarios, and the simulation results demonstrate that the PSO-BOA algorithm outperforms the PSO and BOA in terms of convergence accuracy, with a tracking accuracy of no less than 99.94%. In contrast, the PSO algorithm is prone to becoming trapped in local optima, resulting in a convergence accuracy of only 96.96% when both irradiation and temperature undergo abrupt changes. The PSO-BOA algorithm also surpasses both the PSO and BOA algorithms in handling

oscillations. In terms of convergence time, the PSO-BOA algorithm shows a significant improvement. Particularly, in scenarios of abrupt changes in irradiation and simultaneous changes in temperature and irradiation, the convergence time of PSO-BOA is less than 0.5 s, while the BOA takes approximately double the time compared to the PSO-BOA. Moreover, the convergence time of the PSO algorithm is relatively longer, and it tends to converge quickly but may be trapped in local optima. Therefore, the proposed algorithm exhibits faster convergence speed, higher tracking accuracy, and smaller oscillations compared to both the PSO and BOA algorithms, which can effectively enhance power supply reliability and safety.

**Author Contributions:** Conceptualization, Y.W. and S.D.; methodology, Y.W.; software, S.D.; validation, Y.W. and S.D.; formal analysis, Y.W. and S.D.; investigation, P.L. and X.Z.; resources, P.L.; data curation, P.L. and X.Z.; writing—original draft preparation, S.D.; writing—review and editing, Y.W.; visualization, P.L. and X.Z.; supervision, Y.W.; project administration, P.L. and X.Z.; funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This project was supported by the National Key Research and Development Program "Key Special Project on Intergovernmental Cooperation for National Scientific and Technological Innovation" (2019YFE0197700), the National Natural Science Foundation of China (NSFC) (61673281, 61903264) and Scientific Research Funding Project of Liaoning Province, China (LJKZ0689), and the Natural Science Foundation of Liaoning Province (2019-KF-03-01).

**Data Availability Statement:** Data are unavailable due to privacy.

**Acknowledgments:** The authors sincerely thank the National Key Research and Development Program for their financial support.

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