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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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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
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2021-Jun-30
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2021-Jun-06
SCOPUS published the CiteScore for 2020, computed by using an improved methodology, counting the citations received in 2017-2020 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2020 is 2.5, better than all our previous results.

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  1/2020 - 2

Artificial Immunity Based Wound Healing Algorithm for Power Loss Optimization in Smart Grids

CINAR, M. See more information about CINAR, M. on SCOPUS See more information about CINAR, M. on IEEExplore See more information about CINAR, M. on Web of Science, KAYGUSUZ, A. See more information about KAYGUSUZ, A. on SCOPUS See more information about KAYGUSUZ, A. on SCOPUS See more information about KAYGUSUZ, A. on Web of Science
 
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Download PDF pdficon (474 KB) | Citation | Downloads: 779 | Views: 1,165

Author keywords
smart grids, load flow, optimization methods, power system analysis computing, power system simulation

References keywords
power(35), systems(17), reactive(15), optimal(12), dispatch(10), optimization(9), swarm(8), algorithm(8), electric(6), loss(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-02-28
Volume 20, Issue 1, Year 2020, On page(s): 11 - 18
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.01002
Web of Science Accession Number: 000518392600002
SCOPUS ID: 85083726686

Abstract
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In this study, a human immune system based wound healing algorithm is mentioned to optimize power losses in the smart grids. The smart grids are a concept that uses communication and control techniques to increase the efficiency of today's electrical systems, provide bidirectional communication and allow instant monitoring of the grid. The wound healing algorithm is computationally simulated in the event of a possible injury to the human body and there are very few publications on the proposed algorithm when the literature review is performed. Therefore, the proposed algorithm is capable of removing this gap in the literature. The codes are written in the Matlab GUI environment and applied to the IEEE 30-busbar system and power losses are tried to be optimized. Simulation results show that the actual power loss is significantly reduced. The obtained results were compared with the results of other algorithms that are available in the literature. The proposed wound healing algorithm has given more optimum and superior solutions than the other algorithms compared in terms of calculation time and optimum power loss values and it was emphasized that it was a more effective method in providing the solution.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 3
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Cited-By CrossRef

[1] Adaptive collaborative optimization of traffic network signal timing based on immune-fireworks algorithm and hierarchical strategy, Qiao, Zhimin, Ke, Liangjun, Zhang, Gewei, Wang, Xiaoqiang, Applied Intelligence, ISSN 0924-669X, Issue 10, Volume 51, 2021.
Digital Object Identifier: 10.1007/s10489-021-02256-y
[CrossRef]

[2] Reactive power optimization based on adaptive multi-objective optimization artificial immune algorithm, Lian, Lian, Ain Shams Engineering Journal, ISSN 2090-4479, Issue 5, Volume 13, 2022.
Digital Object Identifier: 10.1016/j.asej.2021.101677
[CrossRef]

[3] Optimal tuning of a PID controller using a wound healing algorithm based on the clonal selection principle, Ç─▒nar, Mehmet, Transactions of the Institute of Measurement and Control, ISSN 0142-3312, Issue 9, Volume 44, 2022.
Digital Object Identifier: 10.1177/01423312211064658
[CrossRef]

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