  To mitigate the vulnerability of distribution grids to severe weather events,
some electric utilities use preemptive de-energization as the primary line of
defense, causing significant power outages. In such instances, networked
microgrids could improve resiliency and maximize load delivery, though the
modeling of three-phase unbalanced network physics and computational complexity
pose challenges. These challenges are further exacerbated by an increased
penetration of uncertain loads. In this paper, we present a two-stage
mixed-integer robust optimization problem that configures and operates
networked microgrids, and is guaranteed to be robust and feasible to all
realizations of loads within a specified uncertainty set, while maximizing load
delivery. To solve this problem, we propose a cutting-plane algorithm, with
convergence guarantees, which approximates a convex recourse function with
sub-gradient cuts. Finally, we provide a detailed case study on the IEEE 37-bus
test system to demonstrate the economic benefits of networking microgrids to
maximize uncertain-load delivery.
