A Spatial-Temporal model for grid impact analysis of plug-in electric vehicles

Mu, Yunfei, Wu, Jianzhong ORCID: https://orcid.org/0000-0001-7928-3602, Jenkins, Nicholas ORCID: https://orcid.org/0000-0003-3082-6260, Jia, Hongjie and Wang, Chengshan 2014. A Spatial-Temporal model for grid impact analysis of plug-in electric vehicles. Applied Energy 114 , pp. 456-465. 10.1016/j.apenergy.2013.10.006

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Abstract

A Spatial–Temporal model (STM) was developed to evaluate the impact of large scale deployment of plug-in electric vehicles (EVs) on urban distribution networks. The STM runs based on the integration of power system analysis and transportation analysis. Origin–Destination (OD) analysis from intelligent transportation research was used to model the EV mobility. Based on the EV technical and market information provided by the EU MERGE project and the output of OD analysis, a Monte Carlo simulation method was developed within the STM to obtain the EV charging load of each load busbar over time. The STM aims to facilitate power system evaluation and planning, and is able to provide both average values and probabilities of nodal bus voltages and branch loadings. The STM is able to identify the critical network components that will require to be upgraded. A high customer density urban network from the United Kingdom Generic Distribution System combined with geographic information was used as a test system. Two EV charging strategies, “dumb” charging and “smart” charging, were simulated and compared under different EV penetration levels (0%, 25% and 50%) to verify the effectiveness of STM.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords:	Electric vehicle (EV); Distribution network; EV charging strategies; Power system planning; Spatial–Temporal model; Origin–Destination matrix.
Publisher:	Elsevier
ISSN:	0306-2619
Funders:	EPSRC, EU FP7
Date of First Compliant Deposit:	30 March 2016
Date of Acceptance:	5 October 2013
Last Modified:	18 May 2023 20:38
URI:	https://orca.cardiff.ac.uk/id/eprint/62485

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