  We compare stochastic programming and robust optimization decision models for
informing the deployment of ad hoc flood mitigation measures to protect
electrical substations prior to an imminent and uncertain hurricane. In our
models, the first stage captures the deployment of a fixed quantity of flood
mitigation resources, and the second stage captures the operation of a
potentially degraded power grid with the primary goal of minimizing load shed.
To model grid operation, we introduce adaptations of the DC and LPAC power flow
approximation models that feature relatively complete recourse by way of an
indicator variable. We apply our models to a pair of geographically realistic
flooding case studies, one based on Hurricane Harvey and the other on Tropical
Storm Imelda. We investigate the effect of the mitigation budget, the choice of
power flow model, and the uncertainty perspective on the optimal mitigation
strategy. Our results indicate the mitigation budget and uncertainty
perspective are impactful whereas choosing between the DC and LPAC power flow
models is of little to no consequence. To validate our models, we assess the
performance of the mitigation solutions they prescribe in an AC power flow
model.
