EV Charging in Case of Limited Power Resource

Rasolonjanahary, Manan’Iarivo Louis, Bingham, Chris, Schofield, Nigel and Bazargan, Masoud (2021) EV Charging in Case of Limited Power Resource. Actuators, 10 (325). ISSN 2076-0825

Full content URL: https://doi.org/10.3390/act10120325

EV Charging in Case of Limited Power Resource
Published Open Access manuscript
actuators-10-00325-1.pdf - Whole Document
Available under License Creative Commons Attribution 4.0 International.

Item Type:Article
Item Status:Live Archive


In the case of the widespread adoption of electric vehicles (EV), it is well known that their
use and charging could affect the network distribution system, with possible repercussions including
line overload and transformer saturation. In consequence, during periods of peak energy demand,
the number of EVs that can be simultaneously charged, or their individual power consumption,
should be controlled, particularly if the production of energy relies solely on renewable
sources. This requires the adoption of adaptive and/or intelligent charging strategies. This paper
focuses on public charging stations and proposes methods of attribution of charging priority based
on the level of charge required and premiums. The proposed solution is based on model predictive
control (MPC), which maintains total current/power within limits (which can change with time) and
imparts real‐time priority charge scheduling of multiple charging bays. The priority is defined in
the diagonal entry of the quadratic form matrix of the cost function. In all simulations, the order of
EV charging operation matched the attributed priorities for the cases of ten cars within the available
power. If two or more EVs possess similar or equal diagonal entry values, then the car with the
smallest battery capacitance starts to charge its battery first. The method is also shown to readily
allow participation in Demand Side Response (DSR) schemes by reducing the current temporarily
during the charging operation.

Keywords:Model predictive control, EV charging infrastructure
Subjects:H Engineering > H230 Transport Engineering
H Engineering > H660 Control Systems
H Engineering > H131 Automated Engineering Design
H Engineering > H630 Electrical Power
Divisions:College of Science > School of Engineering
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ID Code:47502
Deposited On:13 Dec 2021 11:44

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