A NOVEL METHODOLOGY FOR THE RESILIENCE ASSESSMENT OF ELECTRIFIED ROAD TRANSPORTATION SYSTEMS

Abstract

Progression of climate change causes increased exposure of transportation infrastructure to natural hazards. Subsequent decarbonization efforts such as the shift to electric vehicles (EVs) introduce new operational dependencies, which can adversely affect the functionality of road transportation following disruptions. These trends motivate the need for methods to characterize and quantify resilience of electrified transportation systems. This thesis develops a two-stage modeling framework that quantifies resilience using three performance dimensions: travel delays, charging delays and queueing delays. In the first stage a novel traffic assignment model with an integrated energy model and range constraints is formulated to yield equilibrium travel delays and charging demands. In the second stage, these charging demands are used in a Monte Carlo simulation of charging station locations to estimate charging and queueing delays. This methodology was applied to two case study scenarios of Northern Colorado with the prolonged closure of a major roadway, based on conditions during the Cameron Peak wildfire. At 4.52% EV ownership rate, results indicate that the overall performance degradation experienced by EVs is strongly contingent on high-power high-capacity charging facilities remaining operational in the disrupted region. For further analysis disaggregated resilience results inform interventions, which are modeled and evaluated to provide decision support. These findings support the use of disaggregated resilience metrics and the proposed assessment methodology for the identification and evaluation of targeted interventions to mitigate bottlenecks and improve electrified transportation system resilience.