Model predictive control for on–off charging of electrical vehicles in smart grids

Shi, Y; Tuan, HD; Savkin, AV; Poor, HV

Model predictive control for on–off charging of electrical vehicles in smart grids

Shi, Y Tuan, HD Savkin, AV Poor, HV

Permalink

Publisher:: Institution of Engineering and Technology (IET)
Publication Type:: Journal Article
Citation:: IET Electrical Systems in Transportation, 2021, 11, (2), pp. 121-133
Issue Date:: 2021-06-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (905.48 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Shi, Y
dc.contributor.author	Tuan, HD
dc.contributor.author	Savkin, AV
dc.contributor.author	Poor, HV
dc.date.accessioned	2022-04-27T22:27:39Z
dc.date.available	2022-04-27T22:27:39Z
dc.date.issued	2021-06-01
dc.identifier.citation	IET Electrical Systems in Transportation, 2021, 11, (2), pp. 121-133
dc.identifier.issn	2042-9738
dc.identifier.issn	2042-9746
dc.identifier.uri	http://hdl.handle.net/10453/156702
dc.description.abstract	Over the next decade, a massive number of plug‐in electric vehicles (PEVs) will need to be integrated into current power grids. This is likely to give rise to unmanageable fluc-tuations in power demand and unacceptable deviations in voltage. These negative impacts are difficult to mitigate because PEVs connect and disconnect from the grid randomly and each type of PEVs has different charging profiles. This paper presents a solution to these problems that involves coordination of power grid control and PEV charging. The proposed strategy minimises the overall costs of charging and power generation in meeting future increases in PEV charging demand and the operational constraints of the power grid. The solution is based on an on–off PEV charging strategy that is easy and convenient to implement online. The joint coordination problem is formulated by a mixed integer non‐linear programming (MINP) with binary charging and continuous voltage variables and is solved by a highly novel computational algorithm. Its online implementation is based on a new model predictive control method that is free from prior assumptions about PEVs' arrival and charging information. Comprehensive simu-lations are provided to demonstrate the efficiency and practicality of the proposed methods.
dc.language	en
dc.publisher	Institution of Engineering and Technology (IET)
dc.relation	http://purl.org/au-research/grants/arc/DP190102501
dc.relation.ispartof	IET Electrical Systems in Transportation
dc.relation.isbasedon	10.1049/els2.12010
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Model predictive control for on–off charging of electrical vehicles in smart grids
dc.type	Journal Article
utslib.citation.volume	11
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
dc.date.updated	2022-04-27T22:27:38Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	2

Abstract:

Over the next decade, a massive number of plug‐in electric vehicles (PEVs) will need to be integrated into current power grids. This is likely to give rise to unmanageable fluc-tuations in power demand and unacceptable deviations in voltage. These negative impacts are difficult to mitigate because PEVs connect and disconnect from the grid randomly and each type of PEVs has different charging profiles. This paper presents a solution to these problems that involves coordination of power grid control and PEV charging. The proposed strategy minimises the overall costs of charging and power generation in meeting future increases in PEV charging demand and the operational constraints of the power grid. The solution is based on an on–off PEV charging strategy that is easy and convenient to implement online. The joint coordination problem is formulated by a mixed integer non‐linear programming (MINP) with binary charging and continuous voltage variables and is solved by a highly novel computational algorithm. Its online implementation is based on a new model predictive control method that is free from prior assumptions about PEVs' arrival and charging information. Comprehensive simu-lations are provided to demonstrate the efficiency and practicality of the proposed methods.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/156702