Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: May 2024
Next issue: Aug 2024
Avg review time: 57 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


TRAFFIC STATS

2,621,738 unique visits
1,042,106 downloads
Since November 1, 2009



Robots online now
SemanticScholar


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 24 (2024)
 
     »   Issue 2 / 2024
 
     »   Issue 1 / 2024
 
 
 Volume 23 (2023)
 
     »   Issue 4 / 2023
 
     »   Issue 3 / 2023
 
     »   Issue 2 / 2023
 
     »   Issue 1 / 2023
 
 
 Volume 22 (2022)
 
     »   Issue 4 / 2022
 
     »   Issue 3 / 2022
 
     »   Issue 2 / 2022
 
     »   Issue 1 / 2022
 
 
 Volume 21 (2021)
 
     »   Issue 4 / 2021
 
     »   Issue 3 / 2021
 
     »   Issue 2 / 2021
 
     »   Issue 1 / 2021
 
 
  View all issues  


FEATURED ARTICLE

Application of the Voltage Control Technique and MPPT of Stand-alone PV System with Storage, HIVZIEFENDIC, J., VUIC, L., LALE, S., SARIC, M.
Issue 1/2022

AbstractPlus






LATEST NEWS

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.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

Read More »


    
 

  1/2020 - 2

 HIGHLY CITED PAPER 

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
 
View the paper record and citations in View the paper record and citations in Google Scholar
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (474 KB) | Citation | Downloads: 1,052 | Views: 2,083

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
Quick view
Full text preview
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  «-- Click to see who has cited this paper

[1] J. Dongli, X. Meng and X. Song, "Study on technology system of self-healing control in smart distribution grid," International Conference on Advanced Power System Automation and Protection, Beijing, 2011, pp.26-30.
[CrossRef] [SCOPUS Times Cited 47]


[2] X. Fang, S. Misra, G. Xue and D.Yang, "Smart grid-the new and improveds power gird: a survey", IEEE Communication Surveys& Tutorials, vol. 14, no. 4, pp. 944-980, 2012.
[CrossRef] [Web of Science Times Cited 1829] [SCOPUS Times Cited 2386]


[3] M. Cinar and A. Kaygusuz, "Optimum Fuel Cost in Load Flow Analysis of Smart Grid by Using Artificial Bee Colony Algorithm," International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Turkey, 2019, pp. 1-5.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 6]


[4] NIST, NIST framework and roadmap for smart grid interoperability standards, Release 3.0, 2014.

[5] R. P. Guerrero, G. T. Heydt, N. J. Jack, B. K. Keel and A. R. Castelhano, "Optimal Restoration of Distribution Systems Using Dynamic Programming," IEEE Transactions on Power Delivery, vol. 23, no. 3, pp. 1589-1596, 2008.
[CrossRef] [Web of Science Times Cited 97] [SCOPUS Times Cited 137]


[6] A survey: Algorithms stimulating bee swarm intelligence (Karaboga, Akay, 2009).

[7] T. Q. D. Khao and B. T. T. Phan, "Ant colony search-based loss minimum for reconfiguration of distributed systems," IEEE Power India Conference New Delphi, India, 2006, pp.1-6.
[CrossRef] [SCOPUS Times Cited 9]


[8] X. S. Yong and X. He, "Firefly algorithm: Recent advances and applications," International Journal of Swarm Intelligence, vol. 1, pp. 36, 2013.
[CrossRef]


[9] J. C. Cebrian and N. Kagan, "Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms," Electric Power Systems Research, vol. 80, no. 1, pp. 53-62, 2010.
[CrossRef] [Web of Science Times Cited 49] [SCOPUS Times Cited 69]


[10] B. Zhao, C. X. Guo and Y. J. Cao, "A multiagent-based particle swarm optimization approach for optimal reactive power dispatch," IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 1070-1078, 2005.
[CrossRef] [Web of Science Times Cited 399] [SCOPUS Times Cited 523]


[11] W. Yan, S. Lu and D. C. Yu, "A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique," IEEE Transactions on Power Systems, vol. 19, no. 2, pp. 913-918, 2004.
[CrossRef] [Web of Science Times Cited 95] [SCOPUS Times Cited 126]


[12] R. N. S. Mei, M. H. Sulaiman, Z. Mustaffa and H. Daniyal, "Optimal reactive power dispatch solution by loss minimization using moth-flame optimization technique," Applied Soft Computing, vol. 59, pp. 210-222, 2017.
[CrossRef] [Web of Science Times Cited 148] [SCOPUS Times Cited 200]


[13] Y. Mao and M. Li, "Optimal reactive power planning based on simulated annealing particle swarm algorithm considering static voltage stability," International Conference on Intelligent Computation Technology and Automation (ICICTA),Hunan, 2018, pp.106-110.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 16]


[14] Z. Wen and L. Yutian, "Multi-objective reactive power and voltage control based on fuzzy optimization strategy and fuzzy adaptive particle swarm," Electric Power and Energy Systems, vol. 30, no. 9, pp. 525-532, 2008.
[CrossRef] [Web of Science Times Cited 151] [SCOPUS Times Cited 207]


[15] S. Mouassa, T. Bouktir and A. Salhi, "Ant lion optimizer for solving optimal reactive power dispatch problem in power systems," Engineering Science and Technology an International Journal, vol. 20, no. 3, pp. 885-895, 2017.
[CrossRef] [Web of Science Times Cited 142] [SCOPUS Times Cited 200]


[16] D. Chaohua, C. Weirong, Z. Yunfang and Z. Xuexia, "Seeker optimization algorithm for optimal reactive power dispatch," IEEE Transactions on Power Systems, vol. 24, no. 3, pp. 1218-1231, 2009.
[CrossRef] [Web of Science Times Cited 280] [SCOPUS Times Cited 407]


[17] K. Mahadevan and P.S. Kannan, "Comprehensive learning particle swarm optimization for reactive power dispatch," Applied Soft Computing, vol. 10, no. 2, pp. 641-652, 2010.
[CrossRef] [Web of Science Times Cited 197] [SCOPUS Times Cited 254]


[18] P. K. Roy, S. P. Ghoshal and S. S. Thakur, "Optimal VAR control for improvements in voltage profiles and for real power loss minimization using biogeography based optimization," Electric Power and Energy Systems, vol. 43, no. 1, pp. 830-838, 2012.
[CrossRef] [Web of Science Times Cited 54] [SCOPUS Times Cited 79]


[19] K. Ayan and U. Kilic, "Artificial bee colony algorithm solution for optimal reactive power flow," Applied Soft Computing, vol. 12, no. 5, pp. 1477-1482, 2012.
[CrossRef] [Web of Science Times Cited 135] [SCOPUS Times Cited 183]


[20] A. Q. Badar, B. S. Umre and A. S. Junghare, "Reactive power control using dynamic particle swarm optimization for real power loss minimization," Electric Power and Energy Systems, vol. 41, no. 1, pp. 133-136, 2012.
[CrossRef] [Web of Science Times Cited 94] [SCOPUS Times Cited 117]


[21] L. N. de Castro and J.Timmis, "Artificial Immune Systems: A New Computational Intelligence Approach," Springer-Verlag, 2002.

[22] R. Belkacemi and A. Feliachi, "An immune system approach for power system automation and self healing," 2009 IEEE/PES Power Systems Conference and Exposition, Seattle, WA, 2009, pp. 1-7,
[CrossRef]


[23] S. S. F. Souza, R. Romero and J. F. Franco, "Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems," Electric Power Systems Research, vol. 119, pp. 304-312, 2015.
[CrossRef] [Web of Science Times Cited 31] [SCOPUS Times Cited 36]


[24] A. A. Abou El Ela, M. A. Abido and S. R. Spea, "Differential evolution algorithm for optimal reactive power dispatch," Electric Power Systems Research, vol. 81, no. 2, pp. 458-64, 2011.
[CrossRef] [Web of Science Times Cited 200] [SCOPUS Times Cited 264]


[25] S. Duman, Y. Sonmez, U. Guvenc and N. Yorukeren, "Optimal reactive power dispatch using a gravitational search algorithm," IET Generation, Transmission & Distribution, vol. 6, no. 6, pp. 563-576, 2012.
[CrossRef] [Web of Science Times Cited 178] [SCOPUS Times Cited 219]


[26] A. Bhattacharya and P. K. Chattopadhyay, "Solution of optimal reactive power flow using biogeography-based optimization," International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 4, no. 3, pp. 621-629, 2010.

[27] K. Mahadevan and P. S. Kannan, "Comprehensive learning particle swarm optimization for reactive power dispatch," Applied Soft Computing, vol. 10, pp. 641-652, 2010.
[CrossRef] [Web of Science Times Cited 197] [SCOPUS Times Cited 254]


[28] B. Shaw, V. Mukherjee and S. P. Ghoshal, "Solution of reactive power dispatch of power systems by an opposition-based gravitational search algorithm," Electrical Power and Energy Systems, vol. 55, pp. 29-40, 2014.
[CrossRef] [Web of Science Times Cited 152] [SCOPUS Times Cited 194]




References Weight

Web of Science® Citations for all references: 4,443 TCR
SCOPUS® Citations for all references: 5,933 TCR

Web of Science® Average Citations per reference: 153 ACR
SCOPUS® Average Citations per reference: 205 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 2024-06-07 20:42 in 163 seconds.




Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2024
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: 


DNS Made Easy