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JCR Impact Factor: 0.700
JCR 5-Year IF: 0.700
SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Nov 2024
Next issue: Feb 2025
Avg review time: 58 days
Avg accept to publ: 60 days
APC: 300 EUR


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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  1/2018 - 10

 HIGHLY CITED PAPER 

Improving Voltage Profile and Optimal Scheduling of Vehicle to Grid Energy based on a New Method

NAZARLOO, A. See more information about NAZARLOO, A. on SCOPUS See more information about NAZARLOO, A. on IEEExplore See more information about NAZARLOO, A. on Web of Science, FEYZI, M. R. See more information about  FEYZI, M. R. on SCOPUS See more information about  FEYZI, M. R. on SCOPUS See more information about FEYZI, M. R. on Web of Science, SABAHI, M. See more information about  SABAHI, M. on SCOPUS See more information about  SABAHI, M. on SCOPUS See more information about SABAHI, M. on Web of Science, BANNAE SHARIFIAN, M. B. See more information about BANNAE SHARIFIAN, M. B. on SCOPUS See more information about BANNAE SHARIFIAN, M. B. on SCOPUS See more information about BANNAE SHARIFIAN, M. B. on Web of Science
 
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Download PDF pdficon (1,926 KB) | Citation | Downloads: 1,033 | Views: 4,653

Author keywords
discharges (electric), electric vehicles, energy management, optimal scheduling, power grids

References keywords
grid(23), power(14), vehicle(13), electric(10), vehicles(8), energy(7), plug(6), smart(5), hybrid(5), distribution(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 81 - 88
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01010
Web of Science Accession Number: 000426449500010
SCOPUS ID: 85043286801

Abstract
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The electric vehicles (EVs), depending on the charging or discharging modes, can act as flexible loads or as flexible energy sources. Therefore, this paper proposes a method for achieving the following objectives: improvement the voltage profile of the point of common coupling (PCC), control the charging and discharging of EVs in an appropriate scheduling so that at the end of the charging and discharging process all EVs are fully charged, improvement the profiles of active and reactive loads based on the peak shaving and the valley filling, charging rate control and energy management for the economic justification of vehicle to grid (V2G) technology based on the proposed method. Considering that the penetration of EVs and state of charge (SOC) of battery at any time is random, this paper extracts and analyzes the data that is available through national household travel surveys (NHTS). In order to determine the desired parameters, two stochastic algorithms are integrated with Monte Carlo simulations. To prove the performance superiority of the proposed method over conventional methods under high EVs-penetration, an IEEE 14-bus system is used for real-time simulation.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 6
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Cited-By CrossRef

[1] A comprehensive review of demand side management in distributed grids based on real estate perspectives, Dahiru, Ahmed Tijjani, Daud, Dzurllkanian, Tan, Chee Wei, Jagun, Zainab Toyin, Samsudin, Salfarina, Dobi, Abdulhakeem Mohammed, Environmental Science and Pollution Research, ISSN 1614-7499, Issue 34, Volume 30, 2023.
Digital Object Identifier: 10.1007/s11356-023-25146-x
[CrossRef]

[2] Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit, Nimalsiri, Nanduni I., Ratnam, Elizabeth L., Mediwaththe, Chathurika P., Smith, David B., Halgamuge, Saman K., Applied Energy, ISSN 0306-2619, Issue , 2021.
Digital Object Identifier: 10.1016/j.apenergy.2021.116857
[CrossRef]

[3] Real Measure of a Transmission Line Data with Load Fore-cast Model for The Future, YILMAZ, Musa, Balkan Journal of Electrical and Computer Engineering, ISSN 2147-284X, Issue 2, Volume 6, 2018.
Digital Object Identifier: 10.17694/bajece.419646
[CrossRef]

[4] Research on the effect of large-scale electric vehicle based on smart wearable equipment access to grid, Cai, Li, Hu, Pengqiu, Tan, Zefu, Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, Issue 8, Volume 10, 2019.
Digital Object Identifier: 10.1007/s12652-018-1041-7
[CrossRef]

[5] On supply demand coordination in vehicle-to-grid — A brief literature review, Jia, Qing-Shan, 2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC), ISBN 978-1-5386-7255-6, 2018.
Digital Object Identifier: 10.1109/YAC.2018.8406532
[CrossRef]

Updated 2 days, 20 hours ago

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Faculty of Electrical Engineering and Computer Science
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