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University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  4/2021 - 3

Intelligent Charging Control of Power Aggregator for Electric Vehicles Using Optimal Control

ALKAWAZ, A. N. See more information about ALKAWAZ, A. N. on SCOPUS See more information about ALKAWAZ, A. N. on IEEExplore See more information about ALKAWAZ, A. N. on Web of Science, KANESAN, J. See more information about  KANESAN, J. on SCOPUS See more information about  KANESAN, J. on SCOPUS See more information about KANESAN, J. on Web of Science, MOHD KHAIRUDDIN, A. S. See more information about  MOHD KHAIRUDDIN, A. S. on SCOPUS See more information about  MOHD KHAIRUDDIN, A. S. on SCOPUS See more information about MOHD KHAIRUDDIN, A. S. on Web of Science, CHOW, C. O. See more information about  CHOW, C. O. on SCOPUS See more information about  CHOW, C. O. on SCOPUS See more information about CHOW, C. O. on Web of Science, SINGH, M. See more information about SINGH, M. on SCOPUS See more information about SINGH, M. on SCOPUS See more information about SINGH, M. on Web of Science
 
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Download PDF pdficon (1,684 KB) | Citation | Downloads: 486 | Views: 342

Author keywords
battery chargers, electric vehicle, energy consumption, lithium batteries, optimal control

References keywords
electric(18), vehicles(13), charging(11), control(9), vehicle(8), plug(8), optimal(8), smart(7), grid(7), energy(7)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-11-30
Volume 21, Issue 4, Year 2021, On page(s): 21 - 30
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.04003
Web of Science Accession Number: 000725107100003
SCOPUS ID: 85122254802

Abstract
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Electric Vehicles (EVs) have been shown to be better for the environment since they emit lesser air pollutants compared to fuel-based vehicles. High penetration of EVs in the distribution network contributes to the increment of capital investment in smart grid technologies. This is because EVs' charging operation involves a considerably high level of electricity due to the size of EVs' battery charging period. Poor scheduling of EVs charging operation will lead to an increment in electricity consumption. This will then lead to overloading of distribution network, voltage quality degradation, power loss increment, and dispatch of uneconomical energy sources. Hence, coordinated, and smart charging schemes are vital in order to reduce charging costs. This paper proposes an optimized EV battery charging and discharging scheduling model using an ordinary differential equation (ODE) based on three charging scenarios. The daily charging and discharging schedule of EVs are optimized using optimal control. The result shows that the proposed optimized charging and discharging scheduling model reduces the charging cost up to approximately 50%.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 2,662 TCR
SCOPUS® Citations for all references: 3,534 TCR

Web of Science® Average Citations per reference: 95 ACR
SCOPUS® Average Citations per reference: 126 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2022-07-01 16:06 in 155 seconds.




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