Multi-Scale Modeling and Probabilistic Assessment of Electrical Power and Dependent Systems' Resilience to Extreme Events

Electrical power systems and infrastructure systems that depend on electric power are deployed and operated at spatial scales ranging from individual facilities to cities to regions. The resilience of these systems has evolved naturally under the influence of extreme events. This evolution continues today as systems face more severe and frequent extreme events. Accurately representing the present resilience and future evolution of these systems across such a wide range of scales is both a modeling and computational challenge, especially considering that system evolution may involve new technologies and design approaches where no historical data are available to enable extrapolations. Naïve top-down aggregations of existing electrical power distribution networks will not capture important correlations between previous system hardening and critical dependent systems, leading to inaccurate modeling of current local resilience and costs associated with upgrades to improve local resilience and inaccurate boundary conditions on regional-scale electrical transmission models. Using probabilistic risk analysis approaches for hurricane and ice storm events, we present an integrated multi-scale, multi-sector modeling approach that can model and upscale naturally evolved resilience of fine-scale electrical distribution networks and their dependent critical systems. We use stochastic optimization-based models to predict and upscale potential future evolution driven by existing and emerging technologies. An optimization approach can incorporate human factors and represent potential bias in the resilience adaptation toward different residual risk profiles. We describe the coupling of these new aggregated models of fine-scale electrical power system resilience to models of regional electrical transmission systems and show how resilient regional operational strategies may be adapted to autonomous local resilience upgrades.