Multi-Objective Optimization of Operation of Power-Traffic Systems Considering Dynamic Wireless Charging

To reduce the consumption of fossil fuels, improve the environment, and optimize the energy structure, electric vehicles (EVs) have been developed rapidly. At the same time, to alleviate the range anxiety of EV users, the corresponding dynamic wireless charging (DWC) technology has also attracted extensive attention. Driven by EVs and DWC, the interdependency between the power system and transportation system becomes tighter. To improve the operation of the power-traffic system, we propose a multi-objective optimization problem incorporating transportation system congestion, power system generation cost, and total EV user charging cost. Assuming that the energy provided by the DWC can meet the consumption in EV travel, we construct a power demand model for grid buses. Furthermore, we model the microscopic characteristics of vehicle behaviors and propose an adaptive route recommendation algorithm. To solve the multi-objective problem, we adopt a non-dominated sorting genetic algorithm II. Finally, the case studies demonstrate the feasibility of the proposed multi-objective optimization problem and the effectiveness and superiority of the proposed algorithm. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license