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Electric Vehicle Charging on Residential Distribution Systems: Impacts and Mitigations

Open access
Dubey, Anamika, Santoso, Surya·2015·IEEE Access

Abstract

This paper aims to understand, identify, and mitigate the impacts of residential electric vehicle (EV) charging on distribution system voltages. A thorough literature review on the impacts of residential EV charging is presented, followed by a proposed method for evaluating the impacts of EV loads on the distribution system voltage quality. Practical solutions to mitigate EV load impacts are discussed as well, including infrastructural changes and indirect controlled charging with time-of-use (TOU) pricing. An optimal TOU schedule is also presented, with the aim of maximizing both customer and utility benefits. This paper also presents a discussion on implementing smart charging algorithms to directly control EV charging rates and EV charging starting times. Finally, a controlled charging algorithm is proposed to improve the voltage quality at the EV load locations while avoiding customer inconvenience. The proposed method significantly decreases the impacts of EV load charging on system peak load demand and feeder voltages.

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Citations

Cites

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Research works printed but not linked: 57

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Metadata

Authors
Dubey, A., & Santoso, S.
Venue
IEEE Access
Published
2015
Volume
3
Pages
1871-1893
ISSN
2169-3536 (ISSN-L)
OpenAlex
W1943316307
Cited by
475
References
2
FWCI
9.46
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Electric Vehicle Charging on Residential Distribution Systems: Impacts and Mitigations. https://app.cochat.ai/papers/10.1109/access.2015.2476996
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Dubey, A., & Santoso, S. (2015). Electric Vehicle Charging on Residential Distribution Systems: Impacts and Mitigations. IEEE Access. https://doi.org/10.1109/access.2015.2476996

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.