  We consider the worst-case load-shedding problem in electric power networks
where a number of transmission lines are to be taken out of service. The
objective is to identify a pre-specified number of line outage that leads to
the maximum interruption of power generation and load at the transmission
level, subject to the AC power flow model, the load and generation capacity of
the buses, and the phase angle limit across the transmission lines. For this
nonlinear model with binary constraints, we show that all decision variables
are separable except for the nonlinear power flow equations. We develop an
iterative decomposition algorithm, which converts the worst-case load shedding
problem into a sequence of small subproblems. We show that the subproblems are
either convex problems that can be solved efficiently or nonconvex problems
that have closed-form solutions. Consequently, our approach is scalable for
large networks. Furthermore, we prove global convergence of our algorithm to a
critical point and the objective value is guaranteed to decrease throughout the
iterations. Numerical experiments with IEEE test cases demonstrate the
effectiveness of the developed approach.
