Spatial-Temporal Scheduling of Commercial EVs for System Restoration of a Damaged Power-Transportation Coupled Network

Abstract

With large passenger and battery capacity, commercial electric vehicles (CEVs), such as electric buses and electric trucks can act as both urgent transports in transportation networks and energy backup units in power networks after natural disasters cause damages to the power-transportation coupled network. To enhance the system resilience, it is necessary to properly optimize the operation of CEVs to satisfy both the trip demand and restoration requirements of the system. This paper proposes a scheduling strategy for the CEV fleet in a power-transportation coupled network. By scheduling the plug-in locations, charging/discharging profiles, and the navigation paths of the CEV fleet, the model provides energy support for the damaged power network, maximizes the revenue of urgent trip service, and minimizes the energy consumption cost. The coupled power and transportation constraints are explicitly described in the model, which are formulated into a mixed-integer second-order cone program and efficiently solved by off-the-shelf solvers. Numerical experiments are conducted to validate the superiority of the proposed method based on the IEEE 69-bus distribution network and the Sioux Falls transportation network.