A robust resilience improvement method for distribution network based on pre-layout and dynamic scheduling of grid-forming mobile energy storage

To enhance the resilience of distribution networks (DN) against extreme disasters, this paper proposes a robust resilience improvement method based on the pre-layout and dynamic scheduling of grid-forming mobile energy storage (GF-MES). The method follows a pre-disaster defense (PD) and post-disaster recovery (PR) framework. In the PD phase, a two-stage robust optimization (TS-RO) model is formulated considering PV output uncertainty, aiming to optimize both investment costs and load curtailment. The Column-and-Constraint Generation (C&CG) algorithm is used to determine the initial GF-MES deployment plan. In the PR phase, by leveraging the capabilities of GF-MES in frequency regulation and power support and integrating changes in the operation status of the traffic network (TN), a power supply recovery (PSR) model is developed to coordinate GF-MES and electric vehicle stations (EVS). This model is solved as a mixed-integer second-order cone problem (MISOCP) to obtain the optimal scheduling strategy. Finally, simulations are conducted on a modified IEEE 69-bus DN, and the simulation results show that the proposed method can effectively improve the resilience of the DN.