Optimal Assignment of Mobile Charging Stations for On-The-Move Electric Vehicles

Abstract

lectric vehicles (EVs) are gaining increasing interest due to their zero emissions and relatively reduced running cost. However, the availability of charging energy is a main concern for many EV users. Therefore, a mobile charging station (MCS) facility is a potential solution that helps overcome many of the EV charging issues. With MCSs, EVs can be charged more easily with less waiting time compared with traditional fixed charging stations (FCSs). This thesis proposes a new approach to mobile charging stations for electric vehicles. From the perspective of the MCS operator, the goal is to maximize the revenues by increasing the number of served EVs with high required energy among several requests raised to MCS while maintaining a minimum operation cost throughout the charging service. A mobile charging station operating agency (MCSOA) is proposed for running an assignment and dispatching mechanism (ADM). Considering the randomness of EV charging requests and MCS locations, the MCSOA runs a dynamic optimization problem that is formulated as a mixed integer non-linear programming (MINLP) model to assign the most profitable EVs and dispatch the MCS to the optimal charging location, aiming to maximize the total profits of MCSs. Furthermore, the performance of the proposed ADM mechanism has been simulated using real-world traffic flow data of Dubai and Sharjah – UAE. The performance of the proposed system over different system parameters is studied. Additionally, to improve the effectiveness and validity of this mechanism, the system's performance has been evaluated for some irregular conditions, such as road traffic and unbalanced energy demand over the service area. Furthermore, numerical simulations show that the proposed ADM mechanism increases the system profits besides the number of served EVs in comparison with other EV charging coordination approaches including conventional charging at fixed charging stations (FCS), Nearest-Job-Next assignments (NJN), First Come First Served assignments (FCFS) and Earliest Deadline-First (EDF).