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Smart load management of plug-in electric vehicles in distribution and residential networks with charging stations for peak shaving and loss minimisation considering voltage regulation
Abstract
New smart load management (SLM) approach for the coordination of multiple plug-in electric vehicle (PEV) chargers in distribution feeders is proposed. PEVs are growing in popularity as a low emission and efficient mode of transport against petroleum-based vehicles. PEV chargers represent sizeable and unpredictable loads, which can detrimentally impact the performance of distribution grids. Utilities are concerned about the potential overloads, stresses, voltage deviations and power losses that may occur in distribution systems from domestic PEV charging activity as well as from newly emerging charging stations. Therefore this study proposes a new SLM control strategy for coordinating PEV charging based on peak demand shaving, improving voltage profile and minimising power losses. Furthermore, the developed SLM approach takes into consideration the PEV owner preferred charging time zones based on a priority selection scheme. The impact of PEV charging stations and typical daily residential loading patterns are also considered. Simulation results are presented to demonstrate the significant performance improvement offered by SLM for a 1200 node test system topology consisting of several low-voltage residential networks populated with PEVs.
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“It can also cause thermal limit violations of transformers and lines [8], [9].”
From Optimal placement of electric vehicle charging stations in the active distribution network (2020) · cites this paper as [9]
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Metadata
- Authors
- Masoum, A. S., Deilami, S., Moses, P. S., Masoum, M. A. S., & Abu-Siada, A.
- Affiliations
- Operational Asset Management, Western Power, Kewdale, WA 6105, Australia
- Curtin University (AU)
- Department of Electrical and Computer Engineering, Curtin University of Technology, Perth, WA 6845, Australia
- Venue
- IET Generation, Transmission & Distribution
- Published
- 2011-08-08
- Volume
- 5
- Issue
- 8
- Pages
- 877-888
- ISSN
- 1751-8687 (ISSN-L)
- 1751-8695
- OpenAlex
- W2158592959
- Cited by
- 440
- References
- 11
- Citations by year
- 2026: 3 · 2025: 17 · 2024: 17 · 2023: 20 · 2022: 28 · 2021: 31 · 2020: 34 · 2019: 34 · 2018: 31 · 2017: 39 · 2016: 43 · 2015: 41 · 2014: 40 · 2013: 36 · 2012: 23
- FWCI
- 22.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IET Generation Transmission & Distribution (publishedVersion)
- eSpace (Curtin University) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Keywords
- plug-in electric vehicles, electric vehicle charging stations, peak shaving, power loss reduction, voltage regulation, voltage profile, distribution feeders, residential networks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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