Intelligent Path Planning Strategy for Electric Vehicles Combined With Urban Electrified Transportation Network and Power Grid

Abstract

Dynamic wireless power transfer (DWPT), as an emerging technology of coupling the electrified transportation network and power grid, is regarded as a powerful solution for electric vehicles (EVs) promotion. In this article, we propose an intelligent path planning strategy for each individual EV by combining the urban electrified transportation network, power grid, and DWPT. Based on the Floyd algorithm, we ensure the timeliness of path planning by updating the link weights in real time. The EV intelligent path planning strategy comprehensively considers the travel time, charging energy, charging cost, and user convenience. In addition, to ensure that the grid bus voltage has the lowest deviation rate while considering the bus load limit, we propose a multi-stage two-layer optimization algorithm to determine the charging power of each link. The upper layer uses the particle swarm optimization, and the decision variable is the charging power of each link; the lower layer calculates the voltage deviation rate by solving the alternating current optimal power flow model. Finally, the simulation results demonstrate that the intelligent path planning strategy proposed in this article can effectively guarantee a good comprehensive performance in terms of travel time, charging energy, charging cost, and user convenience.