Stochastic Resilient Post-Hurricane Power System Recovery Based on Mobile Emergency Resources and Reconfigurable Networked Microgrids

This paper develops an effective two-stage stochastic post-hurricane recovery framework to improve networked microgrid resilience using mobile emergency resources (MERs) and a proposed reconfiguration strategy. In the first stage, network reconfiguration actively alters the local power flow path and provides opportunities for restoring critical loads, thus reducing the energy not supplied to electric consumers. The optimal schedule determined in the first stage problem is also used to determine the islanded loads that need MERs for restoration. In the second stage, truck-mounted MERs will deliver power to islanded loads, observing the shortest path and post-hurricane transportation infrastructure constraints. Dijkstra’s algorithm is used to produce the shortest path and avoid possible out-of-service roads. In order to model the uncertainties of the problem, a stochastic framework based on unscented transform is employed. The proposed problem is formulated as a two-stage stochastic single-objective optimization problem maximizing system resilience. Simulation results on a test networked microgrid demonstrate the effectiveness and satisfying performance of the proposed model.