Pre-storm scheduling of mobile emergency resources for distribution system restoration considering failure scenario probabilities

With the increasing frequency of extreme weather events, enhancing the resilience and fault recovery capability of distribution systems has become a critical research focus. This paper proposes a pre-storm scheduling and fault restoration method for mobile emergency resources in distribution networks, considering the probabilistic nature of fault scenarios. First, a grid-based fault probability prediction method is developed by integrating storm forecast data with component fragility curves, allowing for the construction of multiple fault scenarios and their associated probabilities. Then, a two-stage optimization framework is proposed. In the first stage, with fixed initial locations of mobile energy storage systems (MESS), a mixed-integer programming model is used to optimize the sequential restoration process. In the second stage, all possible deployment locations of MESS are evaluated, and their configurations are adjusted based on scenario probabilities to determine the optimal pre-disaster positioning strategy. Finally, the proposed method is validated on the IEEE 33-bus distribution system, demonstrating its effectiveness in improving both the efficiency of critical load restoration and the overall system resilience under storm-induced outage conditions.