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dc.contributor.authorDeilami, Sara
dc.contributor.authorMasoum, A.
dc.contributor.authorMasoum, Mohammad
dc.contributor.authorAbu Siada, Ahmed
dc.date.accessioned2017-01-30T14:55:59Z
dc.date.available2017-01-30T14:55:59Z
dc.date.created2013-09-05T20:00:25Z
dc.date.issued2013
dc.identifier.citationDeilami, Sara and Masoum, Amir S. and Masoum, Mohammad A.S. and Abu Siada, Ahmed. 2013. Performance of heuristic optimization in coordination of plug-in electric vehicles charging. International Journal of Renewable Energy & Biofuels International Journal of Sustainable Energy. 2013: pp. 1-15.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/41866
dc.description.abstract

A heuristic load management (H-LMA) algorithm is presented for coordination of Plug-in Electric Vehicles (PEVs) in distribution networks to minimize system losses and regulate bus voltages. The impacts of optimization period T (varied from 15 minutes to 24 hours) and optimization time interval (varied 15 minutes to one hour) on the performance, accuracy and speed of the H-LMA is investigated through detailed simulations considering enormous scenarios. PEV coordination is performed by considering substation transformer loading while taking PEV owner priorities into consideration. Starting with the highest priority consumers, HLMA will use time intervals to distribute PEV charging within three designated high, medium and low priority time zones to minimize total system losses over period T while maintaining network operation criteria such as power generation and bus voltages within their permissible limits. Simulation results generated in MATLAB are presented for a 449 node distribution network populated with PEVs in residential feeders.

dc.publisherIBIMA Publishing
dc.titlePerformance of heuristic optimization in coordination of plug-in electric vehicles charging
dc.typeJournal Article
dcterms.source.volume2013
dcterms.source.startPage1
dcterms.source.endPage15
dcterms.source.titleInternational Journal of Renewable Energy & Biofuels International Journal of Sustainable Energy
curtin.note

This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/ Please refer to the licence to obtain terms for any further reuse or distribution of this work.

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curtin.accessStatusOpen access


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