A Two-Stage Robust Approach for Resilient Unit Commitment With Rail-Based Mobile Energy Storage Under Diffusional Uncertainties

Rail-based mobile energy storage (RMES) provides promising solutions to enhance power system resilience. This paper proposes an extended time-space network (TSN) model to characterize the impact of hurricanes on the rail-based transportation network (RTN). To coordinate the joint operation of the power transmission network and the RTN under a hurricane while considering the diffusional uncertainties about the random failures of the transmission lines and the transportation railway in both systems, a two-stage robust management scheme is presented to minimize the worst-case operating costs of the systems. Specifically, the first stage determines the pre-disaster on/off state of the generator and the pre-planned location of the RMES. In the second stage, the actual charging and discharging actions of RMES based on the proposed extended TSN model will be adjusted by the uncertainty realities to restore the load supply. To solve the developed scheduling model, a customized nested column-and-constraint generation (N-C&CG) algorithm is designed and validated on the IEEE reliability test system (RTS) with a 6-node railway network under hurricane. Case studies illustrate that the proposed RMES strategy can effectively improve power system resilience by exploiting mobility. Compared to classical approaches, the customized nested C&CG algorithm possesses strong sensing capability and computational efficiency.