## 4 Case Study Analysis  
### Simulation Setup  
To quantitatively evaluate the effectiveness of the proposed scheduling strategies, a simulation model is established. As illustrated in Figure 7, the upper panel depicts the coordinated recovery and dispatching center of the power grid, highlighting core functions such as restoring electricity and water supply and coordinating traffic route scheduling through information exchange. The lower panel visualizes the IEEE-33 node system, indicating transmission line damage and community zone layouts. Two distinct resource scheduling schemes are compared: a grouped scheduling approach based on the fast Newman algorithm, which reduces cross-regional dispatch complexity, and a non-grouped (global) scheduling scheme that allocates resources on a system-wide basis. This comparative analysis enables a comprehensive assessment of the impact of regional division on disaster response effectiveness and system resilience. Through experimental calculations, the following emergency resources of two cases are included in the system model. Case 1: Four diesel generators; four small charging stations; four small reservoirs; the number of mobile energy storage vehicles in the four regions is 10, 4, 11, and 8, respectively; the number of mobile water storage vehicles in the four regions is 8, 3, 9, and 7, respectively; the deployment locations of the charging stations are nodes 3, 10, 22, and 28; and the deployment locations of the reservoirs are nodes 1, 5, 13, and 27. Case 2: Four diesel generators; one large charging station; one large reservoir; 24 mobile energy storage vehicles; 21 mobile water storage vehicles. We set the power capacity of one large charging station to be approximately equivalent to that of four small charging stations and the water loading/unloading capacity of  
Figure 7: Transmission line damage and power grid coordination to restore dispatch. one large reservoir to be approximately equivalent to that of four small reservoirs. The charging station and reservoir are deployed at nodes 5 and node 7, respectively. For ease of scheduling, the initial positions of mobile energy storage vehicles and mobile water storage vehicles are set at the charging station and reservoir locations. The main simulation parameters are shown in Table 1.  
In the table, \(E_{e}^{\max}\) and \(E_{w}^{\max}\) represent the maximum carrying capacities of mobile energy storage vehicles and mobile water storage vehicles, respectively; \(SOC_{e}^{\max}\) and \(SOC_{e}^{\min}\) denote the respective maximum and minimum energy capacities of mobile energy storage vehicles; \(SOC_{w}^{\max}\) and \(SOC_{w}^{\min}\) represent the respective maximum and minimum water capacities of mobile water storage vehicles; \(C_{e}^{\rm sd}\) and \(C_{w}^{\rm sd}\) indicate the cost of power generation by diesel generators and the cost of purchasing water resources from reservoirs, respectively; \(C_{e}^{\rm car}\) and \(C_{w}^{\rm car}\) denote the dispatching costs of a single mobile energy storage vehicle and a single mobile water storage vehicle, respectively; \(C_{e}^{\rm stat}\) and \(C_{w}^{\rm res}\) represent the respective costs of constructing a charging station and a reservoir; \(\eta_{e}^{\rm cha}\) and \(\eta_{e}^{\rm dis}\) respectively refer to the charging and discharging efficiency of mobile energy storage vehicles; \(\eta_{w}^{\rm fill}\) and \(\eta_{w}^{\rm dra}\) respectively denote the water loading/unloading efficiency of mobile water storage vehicles; and \(T_{e}^{\rm power}\) and \(T_{w}^{\rm total}\) represent the charging rate of mobile energy storage vehicles and the time required for water loading and unloading, respectively. Throughout the simulation, each time step corresponds to one hour and the assessment horizon spans 48 h after the onset of the ice disaster.