Title: Models for optimal charging scheduling for electric vehicles in smart grid

Authors: Lihui Bai; Guangyang Xu; Nur Dayana Abd Rahman

Addresses: Department of Industrial Engineering, University of Louisville, Louisville, Kentucky 40292, USA ' Department of Industrial Engineering, University of Louisville, Louisville, Kentucky 40292, USA ' Department of Industrial Engineering, University of Louisville, Louisville, Kentucky 40292, USA

Abstract: Electric vehicles have experienced high demand in the market, which will introduce a substantial new load to the current electricity grid. Furthermore, uncontrolled electric vehicle charging from residential users will exacerbate the existing peak load during evening hours. In this paper, we propose optimisation models to alleviate the impact of extra load from electric vehicles on the power grid. Particularly, two centralised models allow the controller to minimise the total electricity costs for all users. Consequently, load levelling of the entire power grid is achieved. On the other hand, a decentralised model allows each user to minimise his/her own electricity cost and studies the resulting system-wide load levelling. Our numerical results indicate significant improvements in the total cost and peak-to-average ratio by both the centralised and decentralised optimal charging scheduling models, when compared to the uncontrolled charging scenarios.

Keywords: electric vehicles; coordinated charging; charging scheduling; demand side management; DSM; mixed integer programming; modelling; optimisation; smart grid; battery charging; load levelling.

DOI: 10.1504/IJOR.2014.064022

International Journal of Operational Research, 2014 Vol.21 No.1, pp.59 - 83

Received: 25 Jul 2012
Accepted: 08 Jan 2013
Published online: 30 Aug 2014 *

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