Predicting voltage unbalance impacts of plug-in electric vehicles penetration in residential low-voltage distribution networks

Shahnia, Farhad, Ghosh, Arindam, Ledwich, Gerard, & Zare, Firuz (2013) Predicting voltage unbalance impacts of plug-in electric vehicles penetration in residential low-voltage distribution networks. Electric Power Components and Systems, 41(16), pp. 1594-1616.

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Abstract

Plug-in electric vehicles will soon be connected to residential distribution networks in high quantities and will add to already overburdened residential feeders. However, as battery technology improves, plug-in electric vehicles will also be able to support networks as small distributed generation units by transferring the energy stored in their battery into the grid. Even though the increase in the plug-in electric vehicle connection is gradual, their connection points and charging/discharging levels are random. Therefore, such single-phase bidirectional power flows can have an adverse effect on the voltage unbalance of a three-phase distribution network. In this article, a voltage unbalance sensitivity analysis based on charging/discharging levels and the connection point of plug-in electric vehicles in a residential low-voltage distribution network is presented. Due to the many uncertainties in plug-in electric vehicle ratings and connection points and the network load, a Monte Carlo-based stochastic analysis is developed to predict voltage unbalance in the network in the presence of plug-in electric vehicles. A failure index is introduced to demonstrate the probability of non-standard voltage unbalance in the network due to plug-in electric vehicles.

Impact and interest:

19 citations in Scopus
15 citations in Web of Science®
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ID Code: 66601
Item Type: Journal Article
Refereed: Yes
Keywords: Distribution network, Plug-in electric vehicle, Sensitivity analysis, Stochastic analysis, Voltage unbalance
DOI: 10.1080/15325008.2013.834004
ISSN: 1532-5008
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Taylor & Francis Group, LLC
Deposited On: 23 Jan 2014 23:17
Last Modified: 29 Jan 2014 03:16

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