## 4 Simulation Results
### Results and Numerical Analysis  
In this paper, the base's sweep load method is modified to consider the dispersed production units. To implement the proposed method, first, the number, type, size, and location of distributed generation units and reactive power sources are obtained. It should be noted that the amount of resource capacity obtained to some extent makes the results more practical with capacities close to it. Since the problem of zoning by the graph to obtain the boundaries of the areas to install the power switch depends on the first step of \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **WT** & **PV** & **FC** \\ \hline Investment \(\cos\t\,(*{\rm kW}^{-1})\) & 1500 & 6675 & - \\ \hline Capacity \(({\rm kW})\) & 750 & 600 & 1000 \\ \hline Annual interest rate & 1 & 1 & - \\ \hline Life span \(({\rm Year})\) & 20 & 20 & - \\ \hline Power factor & 1 & 1 & Variable \\ \hline Fuel \(\cos\t\,(*{\rm kWh}^{-1})\) & 0 & 0 & - \\ \hline Maintenance \(\cos\t\,(*{\rm kWh}^{-1})\) & 0/005 & 0/005 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Distributed production cost data. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type of Load** & **Amount** & **Percentage** & **IEAR** \\ \hline Important \((Active)\) & 5.21 MW & 70\% & 2000 \((\$/{\rm kWh})\) \\ \hline Normal \((Active)\) & 2.23 MW & 30\% & 500 \((\$/{\rm kWh})\) \\ \hline Important \((\)Reactive\()\) & 1.04 MVar & 70\% & 200 \((\$/{\rm KVarh})\) \\ \hline Normal \((\)Reactive\()\) & 0.44 MVar & 30\% & 20 \((\$/{\rm KVarh})\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Initial network load data. the network designer, scenarios are considered, and it cannot be divided into more than four areas. The results will be presented in three scenarios. (A) The first scenario  
The maximum number of areas is divided into four areas. Figure 8 reveals the network under study and the scope of each area. Table 3 presents the locations of distributed generation sources and the location of sources and their size. In this table, the second column shows the location of the scattered products, the third column shows their type, and the fourth column shows their capacity. The fifth column shows the location of reactive power sources, including the capacitor or reactive power injected by the fuel cell, and the last column shows the amount of the reactive power. Table 4 lists the unsupplied energy in each area. The total cost of operation, the expected cost of disconnecting the customer, and the average total loss for operation, in this case, are USD 23.15 billion, USD 2.54 million, and 91.10 kW. Reactive power effects on the depletion of line capacity to improve reliability are considered. Otherwise, the expected cut-off cost will be higher than the actual amount obtained and equal USD 3.12 million. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Microgrid** & \(\textit{ENS}_{\textit{P}}\) & \(\textit{ENS}_{\textit{Q}}\) & \(\textit{EVS}_{\textit{P}}\) & \(\textit{EVS}_{\textit{Q}}\) \\ \hline
1 & 47.32 & 7.18 & 47.18 & 9.32 \\ \hline
2 & 42.72 & 5.03 & 38.53 & 6.45 \\ \hline
3 & 21.95 & 3.43 & 22.07 & 4.57 \\ \hline
4 & 18.74 & 4.65 & 17.84 & 3.53 \\ \hline \hline \end{tabular} (B) The second scenario  
\end{table} 
Table 4: Expected unmet energy supply (in terms of MWh and MVArh ) due to lack of active and reactive power. Figure 8: Network zoning to 4 microgrids. Which each zone in separated with different colors. In this scenario, the network is divided into three areas by changing the initial conjecture. Figure 9 depicts the network under study and the scope of each area. Table 5 presents the locations of distributed generation sources and their types and size. Table 6 lists the unsupplied energy in each area. The total cost of operation, the expected cost of disconnecting the customer, and the average total loss for operation, in this case, are USD 17.12 billion, USD 3.12 million, and 54,029 kW.