Human-safe based electric vehicle evacuation in transportation-power networks during emergencies: A two-stage response framework

Abstract

The proliferation of electric vehicles (EVs) and the deepening interconnection between transportation and the power grid have heightened the complexity and vulnerability of the coupling transportation-power networks (TPNs). EV evacuation can exert significant dynamic pressure on the TPNs during emergencies. This article presents a baseline reproducible two-stage emergency response framework. In the first stage, we develop a platform for the comprehensive simulation called EV evacuation integrated simulation model (EVEISM), utilizing agent-based modeling. The interaction between the agent models and the GIS-based environment models captures the behavior of EVs in the complete evacuation period, including pre-evacuation and post-evacuation charging, receiving notifications, making destination decisions, planning routes to avoid risks, and traffic dynamics. In the second stage, leveraging EVEISM results to enhance situational awareness, strategic pre-positioning of mobile energy storage systems (MESS) and optimal routing are conducted. A mixed-integer second-order cone programming model is established for the coordinated response of multiple power sources to dispatch MESS dynamically. Case studies are conducted on coupling transportation-power systems, exemplified through the toxic gas leak scenario. The numerical results demonstrate the method's effectiveness in ensuring the safe evacuation of residents and optimizing coordinated response to enhance the system's safety and economic efficiency.