  Significant outages from weather and climate extremes have highlighted the
critical need for resilience-centered risk management of the grid. This paper
proposes a multi-stage stochastic robust optimization (SRO) model that advances
the existing planning frameworks on two main fronts. First, it captures
interactions of operational measures with hardening decisions. Second, it
properly treats the multitude of uncertainties in planning. The SRO model
coordinates hardening and system operational measures for smart power
distribution systems equipped with distributed generation units and switches.
To capture the uncertainty in the incurred damage by extreme events, an
uncertainty set is developed by integrating probabilistic information of
hurricanes with the performance of overhead structures. A novel probabilistic
model for the repair time of damaged lines is derived to account for the
uncertainty in the recovery process. A solution strategy based on the
integration of a differential evolution algorithm and a mixed-integer solver is
designed to solve the resilience maximization model. The proposed approach is
applied to a modified IEEE 33-bus system with 485 utility poles and a 118-bus
system with 1841 poles. The systems are mapped on the Harris County, TX, U.S.
Results reveal that optimal hardening decisions can be significantly influenced
by resilience operational measures.
