## 5 Conclusions  
In the planning step for distribution networks, the optimal design of microgrids is a crucial matter. One of the most critical goals in the design of microgrids is to provide a load with the highest reliability and lowest cost. The construction of microgrids in the distribution system has many advantages in minimizing the interaction between the microgrids, preventing the progression of errors, and ultimately increasing the reliability of consumers and distribution companies. In this research study, considering the importance of both cost and reliability aspects, several approaches are created and compared to optimally design the concept of microgrids in an active distribution network. Initially, the distribution system is developed by introducing different types of units, such as wind turbines, solar generators, and fuel cell generators. Due to the nature of renewable sources and hourly load characteristics, these products' appropriate location and size to minimize total losses and cost and reliability criteria are optimally determined. Simultaneously, by using graph theory and obtaining the zoning matrix, the system is divided into optimal microgrids that are modified to consider different areas of the indicators. Since such a problem has its own complexity, the developed Seagull algorithm is used to solve it. In this algorithm, the concept of dynamic archiving with the ability to store non-dominant Pareto answers is used. The roulette cycle method is used to find suitable archived answers. Finally, the proposed method and model for a sample system in different scenarios are discussed. Various zoning scenarios were considered to obtain the best zoning mode and the most reliable microgrid considering the costs. This strategy will make it easier to control each microgrid and protect healthy areas of the network during disruptions. In addition, in most studies, the problem is seen as a single objective using weighting coefficients. However, as can be seen here, the importance of considering the conflict between goals is unavoidable. Therefore, since the third approach provides more choices for the system designer, and it usually makes more sense to consider several goals simultaneously in practice, the third approach is better than the first and second approaches.  
According to the hypothetical errors, the comparison of the corresponding rows in the table above shows that in the programming mode--considering the island capability, for example, \(ENS_{P}\), \(ENS_{Q}\), \(VNS_{Q}\), and \(VNS_{P}\), the index for the first error was improved by 29.67, 31.37, 25.32, and 35.12%, respectively. For other errors, improvements are also observed.  
In future work, the presence of electric vehicles and energy storage resources as equipment used in microgrids to implement demand-side management programs will be discussed. In addition, the environmental pollution along with the economic aspect and reliability can be discussed.  
Figure 12: Convergence of proposed methods to solve the standard test function.  
**Author Contributions:** Conceptualization, Z.W. and X.F.; methodology, X.F.; software, Z.G. and Z.W.; validation, J.F., X.L. and Q.T.; formal analysis, Q.T.; investigation, X.F.; resources, Z.W.; data curation, Z.W.; writing--original draft preparation, Z.W.; writing--review and editing, Z.W.; project administration, X.F. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
We would like to thank the Science and Technology Project of State Grid Sichuan Electric Power Corporation of China (No. 521997200030).  
The authors declare no conflict of interest.