  In recent years, it has become crucial to improve the resilience of
electricity distribution networks (DNs) against storm-induced failures.
Microgrids enabled by Distributed Energy Resources (DERs) can significantly
help speed up re-energization of loads, particularly in the complete absence of
bulk power supply. We describe an integrated approach which considers a
pre-storm DER allocation problem under the uncertainty of failure scenarios as
well as a post-storm dispatch problem in microgrids during the multi-period
repair of the failed components. This problem is computationally challenging
because the number of scenarios (resp. binary variables) increases
exponentially (resp. quadratically) in the network size. Our overall solution
approach for solving the resulting two-stage mixed-integer linear program
(MILP) involves implementing the sample average approximation (SAA) method and
Benders Decomposition. Additionally, we implement a greedy approach to reduce
the computational time requirements of the post-storm repair scheduling and
dispatch problem. The optimality of the resulting solution is evaluated on a
modified IEEE 36-node network.
