Two-Stage Stochastic Scheduling Of Transportable Energy Storage Systems For Resilient Distribution Systems

Transportable energy storage systems (TESSs) provide critical flexibility to enhance the distribution system (DS) resilience. In this paper, a two-stage stochastic restoration scheme is proposed to minimize the total cost. In this model, uncertainties of load consumption and PV power are considered to generate scenarios by using Monte Carlo simulation. A modified temporalspatial network (TSN)-based scheduling model is proposed to schedule TESSs among MGs. The restoration problem is formulated as a mixed-integer linear programming, satisfying self-adequacy, operation and topology constraints. Case studies are implemented on a modified 33-bus test system to demonstrate the effectiveness of the proposed method.