Multi-Source Post-Disaster Recovery with Fuel Cell Vehicles for Distribution Resilience

In response to the urgent need for improving distribution network resilience under frequent extreme natural disasters, a dynamic collaborative recovery strategy incorporating mobile fuel cell vehicles (MFCV) is proposed. First, an emergency response collaborative optimization model is constructed. At the topology reconstruction level, network dynamic partitioning is achieved through remote control switches (RCS), coordinating the spatiotemporal coupling characteristics of preset energy storage systems and MFCV. At the resource scheduling level, an MFCV dynamic scheduling model considering traffic network constraints is established, introducing hydrogen replenishment to characterize MFCV's endurance characteristics. Second, for the bilinear non-convex problem, the original problem is transformed into mixed-integer linear programming (MILP) through linearization methods, while introducing virtual power flow constraints to ensure network radial structure. Finally, comparative experiments based on the improved IEEE 33-node distribution system and coupled traffic network demonstrate that, compared to traditional post-disaster MFCV scheduling schemes, the proposed method can significantly reduce load loss and improve distribution network resilience and economics.