Coordinated operation of coupled transportation and power distribution systems considering stochastic routing behaviour of electric vehicles and prediction error of travel demand

Geng, L; Lu, Z; Guo, X; Zhang, J; Li, X; He, L

Coordinated operation of coupled transportation and power distribution systems considering stochastic routing behaviour of electric vehicles and prediction error of travel demand

Geng, L Lu, Z Guo, X Zhang, J

Li, X He, L

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Publisher:: Institution of Engineering and Technology (IET)
Publication Type:: Journal Article
Citation:: IET Generation, Transmission and Distribution, 2021, 15, (14), pp. 2112-2126
Issue Date:: 2021-07-01

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Field	Value	Language
dc.contributor.author	Geng, L
dc.contributor.author	Lu, Z
dc.contributor.author	Guo, X
dc.contributor.author	Zhang, J https://orcid.org/0000-0003-2616-6722
dc.contributor.author	Li, X
dc.contributor.author	He, L
dc.date.accessioned	2022-04-10T03:59:55Z
dc.date.available	2022-04-10T03:59:55Z
dc.date.issued	2021-07-01
dc.identifier.citation	IET Generation, Transmission and Distribution, 2021, 15, (14), pp. 2112-2126
dc.identifier.issn	1751-8687
dc.identifier.issn	1751-8695
dc.identifier.uri	http://hdl.handle.net/10453/156021
dc.description.abstract	The popularisation of electric vehicles (EVs) and the development of dynamic wireless charging technology have created an emerging trend of transportation electrification, which strengthens the coupling between electrified transportation network (ETN) and power distribution network (PDN). Meanwhile, the stochastic routing behaviour of EVs and prediction error of traffic demand pose a severe challenge to the coordinated ETN-PDN operation problem. This paper proposes a new hybrid optimisation method using stochastic user equilibrium (SUE)/information gap decision theory (IGDT) to study the impact of the unavoidable uncertainties on the coordinated ETN-PDN operation, which consists of the following two stages. In the first stage, a collaborative optimisation model based on SUE and Dist-Flow equations is established to deal with the stochastic EV routing behaviour. Built upon this model, the second stage continues to consider the traffic demand prediction error and establish a risk decision model using IGDT. The proposed model can provide proper road congestion tolls and local generator production schedules to lead to a minimum expected socio-economic cost. Also, two different coordinated operation strategies, that is, risk-seeker and risk-averse strategies, are provided to deal with the uncertainties. Case studies are carried out to demonstrate the effectiveness of the hybrid SUE/IGDT optimisation method.
dc.language	en
dc.publisher	Institution of Engineering and Technology (IET)
dc.relation.ispartof	IET Generation, Transmission and Distribution
dc.relation.isbasedon	10.1049/gtd2.12161
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	Energy
dc.title	Coordinated operation of coupled transportation and power distribution systems considering stochastic routing behaviour of electric vehicles and prediction error of travel demand
dc.type	Journal Article
utslib.citation.volume	15
utslib.for	0906 Electrical and Electronic Engineering
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	2022-04-10T03:59:51Z
pubs.issue	14
pubs.publication-status	Published
pubs.volume	15
utslib.citation.issue	14

Abstract:

The popularisation of electric vehicles (EVs) and the development of dynamic wireless charging technology have created an emerging trend of transportation electrification, which strengthens the coupling between electrified transportation network (ETN) and power distribution network (PDN). Meanwhile, the stochastic routing behaviour of EVs and prediction error of traffic demand pose a severe challenge to the coordinated ETN-PDN operation problem. This paper proposes a new hybrid optimisation method using stochastic user equilibrium (SUE)/information gap decision theory (IGDT) to study the impact of the unavoidable uncertainties on the coordinated ETN-PDN operation, which consists of the following two stages. In the first stage, a collaborative optimisation model based on SUE and Dist-Flow equations is established to deal with the stochastic EV routing behaviour. Built upon this model, the second stage continues to consider the traffic demand prediction error and establish a risk decision model using IGDT. The proposed model can provide proper road congestion tolls and local generator production schedules to lead to a minimum expected socio-economic cost. Also, two different coordinated operation strategies, that is, risk-seeker and risk-averse strategies, are provided to deal with the uncertainties. Case studies are carried out to demonstrate the effectiveness of the hybrid SUE/IGDT optimisation method.

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http://hdl.handle.net/10453/156021