Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit

dc.contributor.authorNimalsiri, Nanduni
dc.contributor.authorRatnam, Elizabeth
dc.contributor.authorMediwaththe, Chathurika
dc.contributor.authorSmith, David
dc.contributor.authorHalgamuge, Saman
dc.date.accessioned2024-03-14T00:43:23Z
dc.date.issued2021
dc.date.updated2022-11-13T07:16:25Z
dc.description.abstractIncreased worldwide uptake of Electric Vehicles (EVs) accentuates the need for developing coordinated EV charging and discharging methods that mitigate detrimental and sustained under-voltage and over-voltage conditions in distribution networks. In this paper, a centrally coordinated EV charge-discharge scheduling method is proposed, referred to as Network-aware EV Charging (and Discharging) N-EVC(D), that takes into account both EV customer economics and distribution grid constraints. Specifically, N-EVC(D) is designed to maintain quasi-steady-state feeder voltages within statutory power quality limits, while minimizing EV customer operational costs associated with: (1) purchasing (or otherwise being compensated for delivering) electricity on a time-of-use tariff; and (2) battery degradation due to frequent charging and discharging. The optimization problem for N-EVC(D) is formulated as a quadratic program, with voltage constraints to limit voltage variability across a radial distribution feeder, and individual EV constraints to satisfy heterogeneous EV charge requirements. In N-EVC(D), each grid-connected EV follows an operator-specified battery schedule that is obtained by solving the proposed quadratic program. A receding horizon implementation is also proposed to support near-real-time N-EVC(D) operations while accommodating non-deterministic EV arrivals and departures. The benefits of N-EVC(D) are assessed by means of numerical simulations carried out on an IEEE test feeder populated with a real-world dataset of residential load collected from households within an Australian distribution network. The simulation results confirm that N-EVC(D) mitigates non-compliant voltage deviations that would otherwise occur when voltage constraints are not enforced. Compared to uncoordinated EV charging, N-EVC(D) offers a 92% ? 111% reduction in the operational costs incurred by EV customers.en_AU
dc.description.sponsorshipNanduni I. Nimalsiri acknowledges the financial support of an Australian National University (ANU) Postgraduate Research Scholarship and a CSIRO Data61 PhD Scholarship.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0306-2619en_AU
dc.identifier.urihttp://hdl.handle.net/1885/315985
dc.language.isoen_AUen_AU
dc.publisherPergamon Pressen_AU
dc.rightsCrown Copyright © 2021 Published by Elsevier Ltd.en_AU
dc.sourceApplied Energyen_AU
dc.subjectElectric vehiclesen_AU
dc.subjectQuadratic programen_AU
dc.subjectReceding horizonen_AU
dc.subjectSupply voltagesen_AU
dc.subjectTime-of-useen_AU
dc.subjectVehicle-to-griden_AU
dc.titleCoordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefiten_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.lastpage12en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationNimalsiri, Nanduni, College of Engineering, Computing and Cybernetics, ANUen_AU
local.contributor.affiliationRatnam, Elizabeth, College of Engineering, Computing and Cybernetics, ANUen_AU
local.contributor.affiliationMediwaththe, Chathurika, College of Engineering, Computing and Cybernetics, ANUen_AU
local.contributor.affiliationSmith, David, College of Engineering, Computing and Cybernetics, ANUen_AU
local.contributor.affiliationHalgamuge, Saman, College of Engineering, Computing and Cybernetics, ANUen_AU
local.contributor.authoruidNimalsiri, Nanduni, u6562870en_AU
local.contributor.authoruidRatnam, Elizabeth, u6837405en_AU
local.contributor.authoruidMediwaththe, Chathurika, u1049257en_AU
local.contributor.authoruidSmith, David, u4593644en_AU
local.contributor.authoruidHalgamuge, Saman, u1029002en_AU
local.description.embargo2099-12-31
local.description.notesImported from ARIESen_AU
local.identifier.absfor490304 - Optimisationen_AU
local.identifier.absfor400805 - Electrical energy transmission, networks and systemsen_AU
local.identifier.ariespublicationa383154xPUB20360en_AU
local.identifier.citationvolume291en_AU
local.identifier.doi10.1016/j.apenergy.2021.116857en_AU
local.identifier.thomsonIDWOS:000640380200003
local.publisher.urlhttps://www.elsevier.com/en_AU
local.type.statusPublished Versionen_AU

Downloads

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
1-s2.0-S0306261921003470-main.pdf
Size:
1.86 MB
Format:
Adobe Portable Document Format
Description:
abcd