Leveraging Electric Vehicles to Enhance Resilience of Interconnected Power-Transportation System Under Natural Hazards

The rapid development of transportation electrification brings about the popularity of interconnected power-transportation systems (IPTSs). However, the escalating frequency and uncertainty of natural hazards, such as typhoons, pose threats, and potential damage to the operation of IPTS. Electric vehicles (EVs) can serve as mobile energy sources, whose proper scheduling in transportation networks can provide power support for the damaged power networks caused by natural hazards, thus enhancing the system’s resilience. This article proposes a two-stage scenario-based scheduling framework using EVs for the restoration of an IPTS under natural hazard risks. In the first stage, EVs are preallocated and precharged at the charging stations (CSs) to maximize their support potential against the predicted hazards; in the second stage, EVs are redispatched to restore the damaged IPTS. To represent the damage of and reduce the computational burden, a scenario generation approach indicating the real hazard’s impact on the IPTS is proposed followed by a scenario-reduction algorithm. The overall revenue using the proposed IPTS model based on the IEEE 33-bus distribution network and the Sioux Falls transportation network outperforms the benchmark by 367.9%. Additional numerical experiments based on the IEEE 123-bus power network are conducted to further validate the scalability of the proposed method.