Research on the Collaborative Restoration Strategy of Distribution-Transportation Network Coupling under Earthquake Disasters

In recent years, the increasingly frequent extreme disasters have brought many challenges to the safety of distribution networks, and it is particularly important to improve the resilience of distribution networks to cope with extreme weather. Firstly, taking earthquakes as representatives of extreme events, a vulnerability model for lines and roads under earthquake disasters is established based on the seismic peak acceleration model; Secondly, the relationship weights of the road network representation structure are determined by defining the relative proximity of nodes, and a spatiotemporal graph of the traffic network is constructed. Based on the extreme learning machine, a mixed optimization model for traffic flow prediction is constructed by embedding a greedy search algorithm; Furthermore, an objective function is constructed from three aspects: important load restoration rate, emergency power supply support capacity, and fault repair capability. The effectiveness of the proposed method is verified through simulation of a 12 node transportation network and an IEEE-33 node distribution network coupled system.