Optimal Planning of Electrified Road Structures Using Queuing Models

Abstract

Dynamic wireless charging (DWC) of electric vehicles (EVs) is an attractive solution to the EV driving range limitations and the associated range anxiety problem. In DWC, charging lanes are deployed along city roads to wirelessly supply the needed charging power to EVs during their motion. However, due to the high construction costs of electrified road structures (ERS) with wireless charging lanes and the likely increase in the energy demand by EV owners, an optimal deployment plan is essential to maximize the net returns to the infrastructure owners and ensure maximal demand coverage. Therefore, to formulate a reliable optimization framework, accurate modeling of the charging lane operation is needed at each potential lane location. In this work, the traffic behavior at different locations is modeled analytically using queuing theory. This accurately represents the desired flow of vehicles on the charging lanes and provides a reliable estimate of the EV charging demand, particularly due to the lack of EV traffic flow datasets with the currently low but expanding penetration of EVs. A multi-objective optimization framework is then developed based on the established traffic model to determine the most optimal locations for the deployment of DWC lanes within a smart city infrastructure. The model is tested on 24 candidate roads selected from the United Arab Emirates map and the corresponding optimal locations are determined by solving the optimization problem on GAMS/CONOPT solver. Sensitivity analysis is also conducted to validate the results of the proposed model.