Abstract
This study researches the dynamical location optimization problem of a mobile charging station (MCS) powered by a LiFePO 4 battery to meet charging demand of electric vehicles (EVs). In city suburbs, a large public charging tower is deployed to provide recharging services for MCS. The EV’s driver can reserve a real-time off-street charging service on the MCS through a vehicular communication network. This study formulates a multi-period nonlinear flow-refueling location model (MNFRLM) to optimize the location of the MCS based on a network designed by Nguyen and Dupuis (1984). The study transforms the MNFRLM model into a linear integer programming model using a linearization algorithm, and obtains global solution via the NEOS cloud CPLEX solver. Numerical experiments are presented to demonstrate the model and its solution algorithm.
Highlights
With economic growth, the rate of world urbanization is continuously accelerating, e.g., China’s urbanization rate grew from 12.84% in 1953 to 58% in 2018 [1]
This study found that the mobile charging station (MCS) relocation rate did not increase significantly with variation in time period, even with the consideration that the traffic flow of the road network increases at a rate of 5% per year
By modeling and solving based on a dynamic location planning of MCSs to capture the largest electric vehicles (EVs) traffic flow, the proposed method is more space -saving than the traditional fixed charging station deployment; (2)
Summary
The rate of world urbanization is continuously accelerating, e.g., China’s urbanization rate grew from 12.84% in 1953 to 58% in 2018 [1]. Previous researcher has studied multiple types of recharging stations for EVs, including the deviation flow refueling location model (DFRLM) and the MFRLM, which are based on the FRLM [25]. This study formulates a new model that considers multiple period equilibrium planning of mobile charging station for EVs. The study extends scenarios of MCS to cover the EV’s path flow and builds on previous studies by Sung Hoon et al and Ying-Wei Wang. The study extends scenarios of MCS to cover the EV’s path flow and builds on previous studies by Sung Hoon et al and Ying-Wei Wang These previous studies researched the maximum coverage of a fixed charging station problem in multi-periods and even evaluated the distinct types of charging facility deployment.
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