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Collaborative optimization of logistics and electricity for the mobile charging service system.

Authors :
Wang, Jiawei
Guo, Qinglai
Sun, Hongbin
Chen, Min
Source :
Applied Energy. Apr2023, Vol. 336, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Mobile charging is proposed as a brand-new charging solution in response to the relatively slow construction of charging facilities. Operating a mobile charging service system involves scheduling mobile charging vehicles (MCVs) and batteries owned by the mobile charging service operator (MCSO), which is important to improve its economic efficiency and has a nonnegligible impact on the power system. In this paper, a bilevel optimization framework for logistics and electricity is developed for MCSOs to achieve joint optimization of planning and operation of the mobile charging service system. For transportation logistics, the upper level plans the size of the MCV fleet and routes MCVs in the dynamic traffic network, which can accommodate dynamic changes in the traffic network and make a reasonable route arrangement. For battery energy management, the lower level plans the battery number and optimizes battery charging and discharging at energy service stations, which can track the electric quantity and the state of each battery during the whole process and accurately describe the matching relationship between batteries in a battery swapping scenario. The upper and lower levels are coupled through the battery swapping behavior between MCVs and energy service stations. Through the iteration and adjustment of the two levels, the results optimize the MCSO's total net profit as much as possible and provide assistance to the power system using service capacity margins. Numerical experiments of a certain scale are used to verify the validity of the proposed framework. • A bilevel optimization framework combines vehicle routing with battery scheduling. • A mobile charging vehicle routing model considers the dynamic traffic network. • An optimization model for battery scheduling tracks each battery's behavior. • Comparison of the proposed framework and benchmarking method using a case study. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03062619
Volume :
336
Database :
Academic Search Index
Journal :
Applied Energy
Publication Type :
Academic Journal
Accession number :
162289125
Full Text :
https://doi.org/10.1016/j.apenergy.2023.120845