## 4 Results and Discussions
### Analysis of Day-Ahead Optimization
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \begin{tabular}{c} **Electricity** \\ **Purchase** \\ **Cost (CNY)** \\ \end{tabular} & \begin{tabular}{c} **Network** \\ **Loss Cost** \\ **(CNY)** \\ \end{tabular} & \begin{tabular}{c} **ESS** \\ **Opera-** \\ **tional Cost** \\ **(CNY)** \\ \end{tabular} & \
\begin{tabular}{c} **Dec** \\ **Network** \\ **Interaction** \\ **Benefit** \\ **(CNY)** \\ \end{tabular} &
\begin{tabular}{c} **Total** \\ **Opera-** \\ **tional Cost** \\ **(CNY)** \\ \end{tabular} \\ \hline Case 1 & 70,232.53 & 2292.63 & 770.57 & 29,128.68 & 44,167.06 \\ Case 2 & 69,866.01 & 2531.04 & 702.80 & 29,129.16 & 43,970.69 \\ Case 3 & 65,698.64 & 2663.45 & 871.75 & 29,136.22 & 40,097.62 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Day-ahead operational costs and benefits under different cases. Figure 5 presents the power equilibrium for the AC2 subnetwork. Comparative analysis reveals that Case 1 (IE, Figure 5a) and Case 2 (CL-CSES, Figure 5b) primarily differ during 1-5 h charging and 19-22 h discharging periods. CL-CSES provides enhanced power time-shifting capability based on leasing larger shared energy storage capacity, storing more electricity during early morning RES surplus periods and releasing more power during evening peak load hours. However, the fixed capacity leasing model restricts its charging/discharging behavior to patterns similar to IE, merely scaled up in magnitude, thus failing to exploit inter-network complementarity potential. In contrast, Case 3 (CO-CSES, Figure 5c) effectively leverages the temporal-spatial complementarity of RES through the coordination framework. During 1-6 h RES surplus periods, the system both accommodates RES through VSC power exchange and stores substantial electricity via CSES. During 9-11 h, CSES discharges to replace VSC exchange, while also providing power support during 17 h and 22 h peak load hours to reduce electricity purchases. As demonstrated in Tables 8 and 9, CO-CSES improves the AC2 subnetwork's RES utilization rate from 85.23% (IE) to 91.07% while significantly reducing total operational costs. As shown in Figure 4, source-load imbalances exist across AC subnetworks, necessitating different energy storage scheduling strategies to achieve peak shaving, valley filling, and cost minimization through optimal power allocation. Figures 6 and 7 show  
Figure 5: Day-ahead power equilibrium of AC2 subnetwork: (**a**) under IE; (**b**) under CL-CSES; (**c**) under CO-CSES. \begin{table}
\begin{tabular}{c c c c} \hline
**Type** & **AC1** & **AC2** & **AC3** \\ \hline Case 1 & 94.55\% & 85.23\% & 99.07\% \\ Case 2 & 94.77\% & 88.61\% & 98.82\% \\ Case 3 & 99.57\% & 91.07\% & 98.82\% \\ \hline \end{tabular}
\end{table} 
Table 9: Day-ahead RES utilization rate of different cases among AC subnetworks. the charging/discharging power and SOC trajectories for all AC subnetworks under the three cases. Figure 4 demonstrates that the AC1 subnetwork has sufficient RES power after 16 h. However, as shown in Figure 6a, inadequate corresponding load results in temporal mismatches, preventing effective time-shifting utilization. Under the CO-CSES (Figure 7b), coordinated optimal scheduling enables surplus energy from the AC1  
Figure 6: Day-ahead ESS charging/discharging power and SOC of each AC subnetwork under IE. (a) AC1; (b) AC2; (c) AC3. Figure 7: Day-ahead CSES charging/discharging power and SOC: (a) under CL-CSES; (b) under CO-CSES. subnetwork to be stored and subsequently dispatched to power-deficient subnetworks, achieving system-wide optimal allocation. Under the CL-CSES (Figure 7a), capacity leasing allocation enhances RES utilization with charging/discharging patterns similar to CO-CSES. However, fixed shared energy storage capacity limits CSES utilization efficiency, as evidenced by SOC trajectories failing to reach upper limits during operational cycles. Notably, all cases maintain operational continuity and safety by ensuring consistent initial/final SOC values while observing safe SOC constraints throughout the scheduling period.