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Stefan cel Mare
University of Suceava
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Computer Science
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ROMANIA

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


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  4/2019 - 7

 HIGH-IMPACT 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: 1,183 | Views: 2,562

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

[1] K. Abaci, V. Yamacli, "Optimal Reactive-Power Dispatch Using Differential Search Algorithm," Electrical Engineering, vol. 99(1), pp. 213-225, 2017.
[CrossRef] [Web of Science Times Cited 37] [SCOPUS Times Cited 53]


[2] J. A. Momoh, J. Z. Zhu, "Improved Interior Point Method For OPF Problems," IEEE Trans. on Power Systems, vol. 14(3), pp. 1114-1120, 1999.
[CrossRef] [Web of Science Times Cited 162] [SCOPUS Times Cited 211]


[3] J. Carpentier, "Contribution a l'etude du Dispatching Economique," Bulletin de la Societe Francaise des Electriciens, vol. 3, pp.431-474, 1962.

[4] A. A. Abou El, M. A. Abido, "Optimal Power Flow Using Tabu Search Algorithm," Electric Power Components and Systems, vol. 30(5), pp. 469-483, 2002.
[CrossRef] [Web of Science Times Cited 297] [SCOPUS Times Cited 396]


[5] R. Mota-Palomino, V. H. Quintana, "Sparse Reactive Power Scheduling By A Penalty-Function Linear Programming Technique," IEEE Transactions on Power Systems, vol. 1(3), pp. 31-39, 1986.
[CrossRef] [Web of Science Times Cited 110] [SCOPUS Times Cited 136]


[6] R. C. Burchett, H. Happ, D. R. Vierath, "Quadratically Convergent Optimal Power Flow," IEEE Trans. on Power Appar. Syst., vol. 103(11), pp. 3264-3276, 1984.
[CrossRef] [Web of Science Times Cited 223] [SCOPUS Times Cited 294]


[7] D. I. Sun, B. Ashley, B. Brewer, A. Hughes, "Optimal Power Flow by Newton Approach," IEEE Trans. Power Appar. Syst., vol. 103(10), pp. 2864-2875, 1984.
[CrossRef] [Web of Science Times Cited 541] [SCOPUS Times Cited 761]


[8] A. Santos, Jr. da Costa, "Optimal Power Flow Solution By Newton's Method Applied To An Augmented Lagrangian Function," IEEE Proc. Gener. Transm. Distrib. Vol 142(1), pp. 33-36, 1995.
[CrossRef] [Web of Science Times Cited 96] [SCOPUS Times Cited 131]


[9] M. Rahli, P. Pirotte, "Optimal Load Flow Using Sequential Unconstrained Minimization Technique Method Under Power Transmission Losses Minimization," Electrical Power System Research, vol 52, pp. 61-64, 1999.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 53]


[10] X. Yan, V.H. Quintana, "Improving An Interior Point Based OPF By Dynamic Adjustments of Step Sizes and Tolerances," IEEE Trans. Power Syst., vol. 14(2), pp. 709-717, 1999.
[CrossRef] [Web of Science Times Cited 138] [SCOPUS Times Cited 197]


[11] V. Veerasamy, R. Ramachandran, M. Thirumeni, B. Madasamy, "Load Flow Analysis Using Generalised Hopfield Neural Network," IET Generation, Transmission & Distribution, vol. 12, pp. 1765-1773, 2017.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 18]


[12] D. Karaboga, B. Akay, "Artificial Bee Colony (ABC) Algorithm on Training Artificial Neural Networks," in Proc. 15th Signal Processing and Communications Applications, Eskisehir, 2007, pp. 128-139.

[13] D. Karaboga, C. Ozturk, "Neural Networks Training By Artificial Bee Colony Algorithm on Pattern Classification," Neural Network World, vol. 19, pp. 279-292, 2009.

[14] J. A. Bullinaria, K. AlYahya, "Artificial Bee Colony Training of Neural Networks: Comparison With Back-Propagation" Memetic Comp. vol. 6, pp. 6-171, 2014.
[CrossRef] [Web of Science Times Cited 24] [SCOPUS Times Cited 32]


[15] T. Olsson, K. Magnusson, "Training artificial neural networks with genetic algorithms for stock forecasting" KTH Royal Institute Of Technology School Of Computer Science And Communication, Stockholm, 2016, vol. 1.

[16] L. Hu, L Q, K. Mao, W. Chen, X. Fu, "Optimization of Neural Network By Genetic Algorithm for Flowrate Determination In Multipath Ultrasonic Gas Flowmeter," IEEE Sensors Journal, vol. 16(5), pp. 1158-1167, 2016.
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 34]


[17] F. Valdez, O. Castillo, P. Melin, "Ant Colony Optimization for the Design Of Modular Neural Networks in Pattern Recognition," in Proc. International Joint Conference on Neural Networks, Canada, 2016, pp. 24-29.
[CrossRef] [SCOPUS Times Cited 10]


[18] C. Juang, Y. Yeh, "Multiobjective Evolution of Biped Robot Gaits Using Advanced Continuous Ant-Colony Optimized Recurrent Neural Networks," IEEE Trans. on Cybernetics, vol. 48(6), pp. 1910-1922, 2018.
[CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 72]


[19] P. Civicioglu, "Transforming Geocentric Cartesian Coordinates to Geodetic Coordinates by Using Differential Search Algorithm," Computers & Geosciences, vol. 46, pp. 229-247, 2012.
[CrossRef] [Web of Science Times Cited 332] [SCOPUS Times Cited 411]


[20] K. Abaci, V. Yamacli, "Differential Search Algorithm for Solving Multi-Objective Optimal Power Flow Problem," International Journal of Electrical Power & Energy Systems, vol. 79, pp. 1-10, 2016.
[CrossRef] [Web of Science Times Cited 153] [SCOPUS Times Cited 198]


[21] T. Kurban, P. Civicioglu, R. Kurban, E. Besdok "Comparison of Evolutionary and Swarm Based Computational Techniques for Multilevel Color Image Thresholding," Applied Soft Computing, vol. 23(1), pp. 128-143, 2014.
[CrossRef] [Web of Science Times Cited 95] [SCOPUS Times Cited 119]


[22] M. A. Gunen, P. Civicioglu, E. Besdok "Differential Search Algorithm Based Edge Detection," in Proc. International Society for Photogrammetry and Remote Sensing Congress, Chezch Republic, 2016, pp. 667-670.

[23] H. M. Marghny, R. M. A. Elaziz, A. I. T. Mohamed, "Differential Search Algorithm-based Parametric Optimization of Fuzzy Generalized Eigenvalue Proximal Support Vector Machine," International Journal of Computer Applications, vol. 108(19), pp. 38-46, 2014.
[CrossRef]


[24] H. Beirami, A. Z. Shabestari, M. M. Zerafat, "Optimal PID Plus Fuzzy Controller Design for a PEM Fuel Cell Air Feed System Using The Self-Adaptive Differential Evolution Algorithm," International Journal of Hydrogen Energy, vol. 40(30), pp. 9422-9434, 2015.
[CrossRef] [Web of Science Times Cited 89] [SCOPUS Times Cited 107]


[25] F. Amato, A. Lopez-Rodriguez, E. M. Pena-Mendez, P. Vanhara, "Artificial Neural Networks in Medical Diagnosis," Journal of Applied Biomedicine, vol. 11(2), pp. 47-58, 2013.
[CrossRef] [Web of Science Times Cited 483] [SCOPUS Times Cited 618]


[26] Z. Comert, A. F. Kocamaz, "A Study of Artificial Neural Network Training Algorithms for Classification of Cardiotocography Signals," Journal of Science and Technology, vol. 7(2), pp. 93-103, 2017.

[27] C. Ozturk, D. Karaboga, "Hybrid Artificial Bee Colony Algorithm for Neural Network Training," in Proc. IEEE Congress of Evolutionary Computation, USA, 2011, pp. 84-88.
[CrossRef] [SCOPUS Times Cited 156]


[28] R. D. Zimmerman, C. E. Murillo-Sanchez, R. J. Thomas, "Matpower: Steadystate Operations, Planning and Analysis Tools for Power Systems Research and Education," IEEE Trans. Power Syst, vol. 26(1), pp. 12-19, 2011.
[CrossRef] [Web of Science Times Cited 4515] [SCOPUS Times Cited 5410]


[29] P. W. Sauer, M. A. Pai, "Power System Dynamics and Stability", pp. 218-293, Prentice Hall, 1998.

[30] T. B. Nguyen, M. A. Pai, "Dynamic Security-Constrained Rescheduling of Power Systems Using Trajectory Sensitivities," IEEE Trans. Power Syst., vol. 18(2), pp. 848-54, 2003.
[CrossRef] [Web of Science Times Cited 193] [SCOPUS Times Cited 260]


[31] O. Alsac, B. Sttot, "Optimal Load Flow with Steady State Security," IEEE Trans. Power Appar. Syst., vol. 93, pp. 745-751, 1974.
[CrossRef] [SCOPUS Times Cited 716]


[32] I. Pena, C. B. Martinez-Anido, B. M. Hodge, "An Extended IEEE 118-Bus Test System with High Renewable Penetration," IEEE Trans. Power Syst., vol. 33(1), pp. 281-289, 2018.
[CrossRef] [Web of Science Times Cited 150] [SCOPUS Times Cited 178]




References Weight

Web of Science® Citations for all references: 7,781 TCR
SCOPUS® Citations for all references: 10,571 TCR

Web of Science® Average Citations per reference: 236 ACR
SCOPUS® Average Citations per reference: 320 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 2024-12-11 15:34 in 169 seconds.




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