Spatial-Temporal Scheduling of Electric Bus Fleet in Power-Transportation Coupled Network

With large passenger and battery capacity, electric buses (EBs) can play dual roles-commuting tools in transportation networks and mobile energy storage units in power networks. To promote the beneficial synergy between power-transportation coupled networks, it is necessary to properly optimize the operation of EBs in both networks. This article proposes a spatial-temporal scheduling framework for the EB fleet in a power-transportation coupled network. By scheduling the plug-in locations and charging/discharging profiles of the EBs, the model not only minimizes the total operational costs of the fleet (i.e., the electricity consumption and battery degradation costs), but also maximizes the revenue by providing flexibility to the power network. The coupled power and transportation constraints are explicitly described in the model. To address the uncertainty from the fleet's energy consumption, chance-constrained programming is adopted that can be reformulated into second-order cones and efficiently solved by off-the-shelf solvers. Numerical experiments are conducted to validate the superiority of the proposed method based on the IEEE 33-bus distribution network and the Sioux Falls transportation network.