**7. Conclusions**

This paper presents an optimal sizing of an islanded microgrid, optimized by dynamic optimization with GWO. The considered microgrid is a small autonomous system that integrates a variety of clean energy distributed power generation systems, energy storage systems, backup power sources, and electrical loads. Due to the complexity of optimal scheduling, a multi-objective optimal scheduling method combining GWO and dynamic optimal scheduling is proposed. Moreover, a comparison between the optimization capabilities of GWO and PSO on the one hand, and the system is divided into six di fferent scenarios for comparison on the other, in order to understand the best output that achieves the lowest total cost of microgrid system operation and the highest clean energy utilization rate. Meteorological data is used, which is measured by the local meteorological bureau, in addition to artificial neural networks used to predict wind and solar energy in the future for a residential area in Sanya, China. The results show that the advantage of combining the GWO solution in optimizing multi-objective problems lies in that it reduces the calculation time and obtains the best function value compared with the PSO method alone. Furthermore, the findings of the study illustrate the economic and environmental feasibility of starting diesel generators under heavy load demand. Using ess as storage can better play the role of peak and valley filling, thereby reducing the total cost of the system. By considering diesel generators as part of the hybrid power system, the utilization of renewable energy can be improved. However, the use of diesel generators will produce polluting gas emissions. To solve this problem, multi-objective optimization based on GWO is applied. The optimal scale of the hybrid system including PV/wind/ess/diesel generators is a total cost of \$64961 and 71070 kg.

In the future, the multi-objective optimization problem of microgrid can be further studied. Secondly, this paper studies the dynamic optimal dispatching of islanded microgrid. The economics of grid-connected microgrid and the utilization rate of clean energy generation must be studied in depth. Finally, because we use GWO for optimization, we can make the method more competitive by adjusting the scheduling strategy.

**Author Contributions:** Y.W. and C.L. supervised the work, Y.W. conceived the idea. Y.W., C.L., K.Y. performed the research. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Natural Science Foundation of China, gran<sup>t</sup> number 51307074. And The APC was funded by Jiangsu University of Science and Technology.

**Acknowledgments:** This work is supported by the National Natural Science Foundation of China (51307074), Jiangsu Provincial Natural Science Foundation of China (BK20130466), Jiangsu University of Science and Technology Graduate Education Teaching Reform Project (103080605).

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