## 5 Result Analysis and Discussion
### Analytical Insights and Discussion (Unveiling the Findings)
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Bus Number**} & \multicolumn{3}{c}{**Optimal State of Dis/Charging (kWh) of BSSs**} & \multicolumn{3}{c}{**Optimal State of Dis/Charging (kWh) of BSSs**} \\  & **at Different Percentages of Nominal Load** & \multicolumn{3}{c}{**Bus Number**} & \multicolumn{3}{c}{**at Different Percentages of Nominal Load**} \\ \cline{2-9}  & **20\%** & **50\%** & **100\%** & **150\%** & \multicolumn{3}{c}{**20\%**} & **50\%** & **100\%** & **150\%** \\ \hline
1 & 0 & 250 & 0 & 0 & 17 & 250 & 0 & 0 & 250 \\
2 & 0 & 0 & 0 & 0 & 18 & 0 & \(-\)250 & 250 & 250 \\
3 & \(-\)250 & \(-\)250 & 250 & \(-\)250 & 19 & 0 & 250 & 250 & 0 \\
4 & \(-\)250 & 0 & 0 & 140.857 & 20 & 250 & 250 & 0 & 250 \\
5 & 0 & 0 & \(-\)250 & 0 & 21 & 0 & 0 & \(-\)161.55 & 0 \\
6 & \(-\)250 & 250 & 250 & \(-\)250 & 22 & 250 & 250 & 0 & 0 \\
7 & 0 & \(-\)250 & 0 & 0 & 23 & \(-\)250 & 250 & \(-\)250 & 250 \\
8 & \(-\)250 & 0 & \(-\)250 & 64.5045 & 24 & 0 & 0 & 0 & 0 \\
9 & 250 & 0 & \(-\)250 & \(-\)250 & 25 & 0 & 0 & 0 & 0 \\
10 & 0 & 0 & 0 & 0 & 26 & 0 & \(-\)250 & 0 & \(-\)250 \\
11 & \(-\)250 & \(-\)250 & \(-\)250 & 0 & 27 & \(-\)96.052 & 0 & \(-\)250 & \(-\)250 \\
12 & 0 & 0 & 0 & \(-\)250 & 28 & 0 & \(-\)76.418 & 0 & 0 \\
13 & 0 & \(-\)250 & \(-\)250 & 0 & 29 & \(-\)250 & 250 & \(-\)250 & 250 \\
14 & 0 & 0 & 250 & 0 & 30 & 250 & 0 & 250 & 0 \\
15 & \(-\)250 & \(-\)250 & \(-\)250 & 120.263 & 31 & 250 & 0 & \(-\)250 & \(-\)250 \\
16 & 0 & 250 & 0 & 0 & 32 & \(-\)250 & 0 & 0 & 0 \\  & & & & & 33 & 0 & 0 & 250 & \(-\)250 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Detailed outcomes outlining the optimal placement of BSSs within the IEEE 33-bus network for varying percentages of load. Figure 20: Optimal state of dynamic coupled switches in IEEE 118-bus network within different load factors. Figure 21: Optimal state of dynamic coupled switches in IEEE 69-bus network within different load factors. Figure 22: Optimal state of dynamic coupled switches in IEEE 33-bus network within different load factors. Furthermore, Tables 5-7 were meticulously compiled to showcase a comprehensive analysis of the proposed methodology's performance compared to existing approaches. The comparison covers various key metrics such as economic viability, power quality improvements, reliability enhancements, and network security considerations. These tables offer a detailed evaluation of the optimal BSS placement program's effectiveness over the study period within the IEEE 118-, 69-, and 33-bus networks, providing valuable insights into the overall impact and benefits of the proposed method. The analysis of the simulation results from the IEEE 33-, 69-, and 118-bus test systems, detailed in Tables 5-7, underscores the superiority of the proposed method over existing approaches in both economic and technical network metrics. This achievement is particularly remarkable given the historical oversight of reliability and power quality indicators in prior studies. The innovative methodology effectively optimizes distributed generation control within the distribution network and intelligent microgrids, notably by strategically managing the operation, such as the charging and discharging of BSSs at key locations and dynamically switching energy paths in power line transmission. For example, the evaluation presented in Tables 5-7 reveals that the energy storage systems in the IEEE 118-, 69-, and 33-bus networks were charged during periods of low demand, typically ranging from 20% to 150% of nominal load. This strategic charging aligns technical aspects like