Load restoration strategy for post-disaster distribution networks considering cyber-physical-traffic coupling with multi-resource collaboration

Extreme events can trigger coupled failures across distribution, information, and traffic networks, thereby compromising the safe operation of distribution networks. Mobile energy storage systems (MESS) provide spatiotemporal flexibility in energy supply and operate in a complementary manner to fixed power sources. Unmanned aerial vehicles (UAVs) offer mobile communication capabilities and facilitate rapid communication recovery. Additionally, fault repair can achieve stepwise load restoration through dynamic network reconfiguration. However, the integrated scheduling of these emergency resources across interdependent systems remains an urgent research challenge. Therefore, this paper proposes a post-disaster load restoration strategy for distribution networks, incorporating multi-resource collaborative scheduling under cyber-physical-traffic coupled failure scenarios. First, a cyber-physical-traffic coupled failure architecture is established. Second, the impact of traffic network failures on vehicle routing is considered, and Dijkstra's algorithm is employed to compute travel times. Simultaneously, to address the reduction in situational awareness and control caused by information network failures, a Location Set Covering Problem (LSCP) algorithm is adopted to optimize UAV site selection. A collaborative scheduling model is subsequently developed, integrating ESS, GAS, MESS, UAVs, and fault repair. The model aims to minimize both load shedding and the cost of emergency resource scheduling, using a multi-timeframe optimization approach to dynamically determine MESS deployment locations and fault repair sequences. Finally, simulations based on a modified IEEE-33-bus distribution system demonstrate that the proposed strategy can effectively reduce post-disaster load losses and shorten load restoration times.