EconPapers    
Economics at your fingertips  
 

A game theory based scheduling approach for charging coordination of multiple electric vehicles aggregators in smart cities

Javad Modarresi, Ali Ahmadian, Ali Diabat and Ali Elkamel

Energy, 2024, vol. 313, issue C

Abstract: In this paper, a game theory-based coordination approach is presented to find the minimum operation cost of multiple electric vehicle (EV) aggregators that are connected to the upstream network. In order to provide a comprehensive study, various EVs aggregators, including residential, commercial, official, university, and industry parking lots, have been considered and the proposed game theory is utilized to coordinate the charging power from/to different microgrids and/or upstream network. In addition of operation cost, a reliability index, service charge and power loss are included in the objective function. The proposed approach is applied on an electricity network with 7 connected microgrids, and different scenarios have been investigated. The simulation results show the overall operation cost in the coalition operation mode is globally minimized in comparison with the non-coalition operation mode. In addition, the reliability index, service charge and power loss force the aggregators to buy their necessary power from the nearby microgrids. The average network loss in the coalition and non-coalition modes are 2.88 % and 4.28 %, respectively. Moreover, the average reliability cost in coalition and non-coalition modes are $2.65 and $4.25, respectively.

Keywords: Game theory; Electric vehicles; Charging coordination; Smart grid; Smart cities (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544224034522
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224034522

DOI: 10.1016/j.energy.2024.133674

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-05-25
Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224034522