A resilience-oriented two-stage recovery method for power distribution system considering transportation network

Abstract

In recent years, extreme weather events have resulted in a number of severe power outages and economic losses. It is becoming urgent to study approaches to enhance power distribution system resilience. This paper presents a two-stage optimization method for improving resilience of power distribution systems. The two-stage method is influenced by a transportation network, which considers the interdependence between traffic roads and overhead distribution lines. In the first stage, based on the Bayesian network and the Monte Carlo method, the locations of emergency stations, e.g., charging stations and repair stations are pre-positioned to improve the recovery speed of interrupted loads after disasters. Then the second stage is to co-optimize the dispatch of mobile energy storage systems and repair crews on transportation network to minimize the shedding of critical loads while considering operation constraints of power, voltage and power flow for power distribution system. The dispatch of mobile energy storage systems and repair crews are affected by the locations of emergency stations in the first stage. The route of mobile energy storage systems and repair crews on transportation network can be obtained from the results in the second stage. The proposed method is tested on a modified IEEE 33-bus distribution test system with a corresponding transportation network. Simulation results demonstrate the effectiveness of the proposed method in enhancing power distribution system resilience by pre-positioning emergency stations and co-dispatching mobile energy storage systems and repair crews.