Abstract:

High-quality navigation and charging scheduling strategies must depend on the state of the coupled network between the transportation and power networks, while the outcomes of scheduling can also have a significant impact on these networks. In this paper, the authors propose a novel dynamic navigation and charging strategy that fully considers the coupled traffic and power distribution networks. Firstly, electric vehicles with similar travel and charging requirements are classified. Secondly, an elastic scheme including fixed route navigation and flexible charging scheduling at charging stations is provided. The authors also propose an information integration framework for the implementation of electric vehicle routing and charging scheduling, information interaction between sectors, including the status of heterogeneous electric vehicles, day-ahead power scheduling, and base load demands. The study proposes a new strategy for optimizing electric vehicle navigation and charging at the system level, aiming to reduce travel, charging, carbon emissions, and load variance. The strategy uses classification algorithms, stochastic dynamic programming, and queuing theory, with numerical results demonstrating its effectiveness.