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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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  4/2019 - 7

 HIGHLY CITED PAPER 

Hybrid Artificial Neural Network by Using Differential Search Algorithm for Solving Power Flow Problem

ABACI, K. See more information about ABACI, K. on SCOPUS See more information about ABACI, K. on IEEExplore See more information about ABACI, K. on Web of Science, YAMACLI, V. See more information about YAMACLI, V. on SCOPUS See more information about YAMACLI, V. on SCOPUS See more information about YAMACLI, V. on Web of Science
 
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Download PDF pdficon (500 KB) | Citation | Downloads: 767 | Views: 1,282

Author keywords
heuristic algorithms, iterative methods, neural networks, optimization, power system analysis computing

References keywords
power(23), neural(13), algorithm(11), optimal(9), networks(8), flow(8), artificial(7), training(6), systems(6), search(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-11-30
Volume 19, Issue 4, Year 2019, On page(s): 57 - 64
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.04007
Web of Science Accession Number: 000500274700006
SCOPUS ID: 85077289267

Abstract
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Power flow (PF) is in one of the most studied non-linear problems related to power systems which heavily affects security issues such as generation cost, voltage stability and active power loss. In this paper, a simple and new approach based on artificial neural network (ANN) and differential search (DSA) algorithm has been proposed and applied for one of the most complex problems in power systems, Power Flow (PF) problem. By using the proposed DSA implemented ANN method, IEEE 9-bus, IEEE 30-bus and IEEE 118-bus test system parameters are obtained without running iterative convergence methods such as Gauss-Siedel or Newton-Raphson. By comparing with several most used non-linear iterative methods, the results obtained using the classical training method and proposed DSA implemented hybrid training methods are presented and discussed. Obtained results in this work show that the ANN based power flow method can be implemented to solve non-linear static and dynamical problems concerning power systems successfully.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 11
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Cited-By CrossRef

[1] Algorithm for power systems mode optimization taking into account the frequency change in terms of probablistic nature of initial information, Gayibov, T, Latipov, Sh, Abdurashidov, D, Pulatov, B, Davirov, A, IOP Conference Series: Materials Science and Engineering, ISSN 1757-8981, Issue 1, Volume 883, 2020.
Digital Object Identifier: 10.1088/1757-899X/883/1/012185
[CrossRef]

[2] Algorithm for optimization of power system short-term mode in conditions of partial uncertainty of initial information taking into account the frequency change, Gayibov, Tulkin, Voropai, N., Senderov, S., Michalevich, A., Guliev, H., E3S Web of Conferences, ISSN 2267-1242, Issue , 2020.
Digital Object Identifier: 10.1051/e3sconf/202021601100
[CrossRef]

[3] Optimal converter control for PV-fed DC and AC interconnection by using hybrid artificial neural networks, Yamacli, Volkan, Abaci, Kadir, Journal of Computational Design and Engineering, ISSN 2288-5048, Issue 1, Volume 8, 2021.
Digital Object Identifier: 10.1093/jcde/qwaa073
[CrossRef]

[4] Development of an algorithm to train artificial neural networks for intelligent decision support systems, Sova, Oleg, Turinskyi, Oleksandr, Shyshatskyi, Andrii, Dudnyk, Volodymyr, Zhyvotovskyi, Ruslan, Prokopenko, Yevgen, Hurskyi, Taras, Hordiichuk, Valerii, Nikitenko, Anton, Remez, Artem, Eastern-European Journal of Enterprise Technologies, ISSN 1729-4061, Issue 9 (103), Volume 1, 2020.
Digital Object Identifier: 10.15587/1729-4061.2020.192711
[CrossRef]

[5] Silicon on Insulator C-VTFET Based Design of low Complexity Sparse Quadrature Mirror Filter Using Differential Search Algorithm, Singh, Hitendra, Dwivedi, Atul Kumar, Nagaria, Deepak, Silicon, ISSN 1876-990X, 2022.
Digital Object Identifier: 10.1007/s12633-022-01858-6
[CrossRef]

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