Power Flow Analysis by Artificial Neural Network

Serhat Berat EFE; Mehmet CEBECİ

doi:doi:10.11648/j.ijepe.20130206.11

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Power Flow Analysis by Artificial Neural Network

Serhat Berat EFE, Mehmet CEBECİ

Published in International Journal of Energy and Power Engineering (Volume 2, Issue 6)

Received: 30 October 2013 Published: 30 November 2013

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Abstract

Computer based methods used to analysis the power systems are developed instead of the steady state of mathematical methods. By the development of computer technology, solution of the network problems gets easier. Increment of the necessity to electrical energy by the development of technology, whereas the increment rate of raw energy sources doesn’t enough, it have made it mandatory to use the energy sources efficiently. Interconnected networks formed by the connection between not only the domestic sources and customers, but also between the different countries for the optimization and for the efficient use of the sources. Electrical engineers faced by the planning and optimization problems of developing interconnected networks. By this way, the requirement of the use of intelligent systems and computer analysis of power systems has become inevitable. In this study, power flow analysis the of a power system that consist five busbars performed by designed neural network. Results are compared by the results that gained by the analysis with classic Gauss- Seidel method of the same system, then the success of the neural network is investigated.

Published in	International Journal of Energy and Power Engineering (Volume 2, Issue 6)
DOI	10.11648/j.ijepe.20130206.11
Page(s)	204-208
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Power Flow Analysis, Artificial Neural Networks, Gauss-Seidel Method

References

[1]	S. Madan and K.E. Bollinger, "Neural Network Based Power Flow Predictor", IEEE Canadian Conference on Electrical and Computer Engineering,1999, pp.1331-1334
[2]	A. Jain, S.C. Tripathy and R. Balasubramanian, "Neural Network Based Stochastic Load Flow Analysis", International Conference on Power System Technology,2004, pp.1845-1850
[3]	H.H. Müller and J.M. Rider, "Power Flow Model Based on Artificial Neural Networks", , IEEE Russia Powertech, 2005, pp.1-6
[4]	L. Powell, Power System Load Flow Analysis, McGraw-Hill, 2004, USA.
[5]	Y. Hase, Handbook of Power System Engineering, John Wiley and Sons, 2007, USA
[6]	N. Kumar, R. Wangneo, P.K. Kalra and S.C. Srivastava, "Application Of Artificial Neural Networks To Load Flow Solutions," IEEE Transactions on Power Systems, 1995, pp.199-203.
[7]	W.S. McCulloch and W. Pitts, "A Logical Calculus of The Ideas Immanent in Nervous Activity", Bull. Math. Biophys, 5, 1943, pp.115-133
[8]	M. İnal and F. Aras, "Yalıtkan Malzemelerin Dielektrik Özelliklerinin Yapay Sinir Ağlarıyla Belirlenmesi", Gazi Üniv. Müh. Mim. Fak. Der, Cilt 20, No 4, 2005, pp.455-462
[9]	S.B. Efe, Güç Akışı Analizi Yöntemleri ve Uygulamaları, PhD. Seminar, 2010,Fırat University, Elazig, Turkey
[10]	H.Shi, Y.Gao and X.Wang, "Optimization of injection molding process parameters using integrated artificial neural network model and expected improvement function method", Int J Adv Manuf Technol, pp.955-962, 2010

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APA Style

Serhat Berat EFE, Mehmet CEBECİ. (2013). Power Flow Analysis by Artificial Neural Network. International Journal of Energy and Power Engineering, 2(6), 204-208. https://doi.org/10.11648/j.ijepe.20130206.11

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ACS Style

Serhat Berat EFE; Mehmet CEBECİ. Power Flow Analysis by Artificial Neural Network. Int. J. Energy Power Eng. 2013, 2(6), 204-208. doi: 10.11648/j.ijepe.20130206.11

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AMA Style

Serhat Berat EFE, Mehmet CEBECİ. Power Flow Analysis by Artificial Neural Network. Int J Energy Power Eng. 2013;2(6):204-208. doi: 10.11648/j.ijepe.20130206.11

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@article{10.11648/j.ijepe.20130206.11,
  author = {Serhat Berat EFE and Mehmet CEBECİ},
  title = {Power Flow Analysis by Artificial Neural Network},
  journal = {International Journal of Energy and Power Engineering},
  volume = {2},
  number = {6},
  pages = {204-208},
  doi = {10.11648/j.ijepe.20130206.11},
  url = {https://doi.org/10.11648/j.ijepe.20130206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20130206.11},
  abstract = {Computer based methods used to analysis the power systems are developed instead of the steady state of mathematical methods. By the development of computer technology, solution of the network problems gets easier. Increment of the necessity to electrical energy by the development of technology, whereas the increment rate of raw energy sources doesn’t enough, it have made it mandatory to use the energy sources efficiently. Interconnected networks formed by the connection between not only the domestic sources and customers, but also between the different countries for the optimization and for the efficient use of the sources. Electrical engineers faced by the planning and optimization problems of developing interconnected networks. By this way, the requirement of the use of intelligent systems and computer analysis of power systems has become inevitable. In this study, power flow analysis the of a power system that consist five busbars performed by designed neural network. Results are compared by the results that gained by the analysis with classic Gauss- Seidel method of the same system, then the success of the neural network is investigated.},
 year = {2013}
}

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TY  - JOUR
T1  - Power Flow Analysis by Artificial Neural Network
AU  - Serhat Berat EFE
AU  - Mehmet CEBECİ
Y1  - 2013/11/30
PY  - 2013
N1  - https://doi.org/10.11648/j.ijepe.20130206.11
DO  - 10.11648/j.ijepe.20130206.11
T2  - International Journal of Energy and Power Engineering
JF  - International Journal of Energy and Power Engineering
JO  - International Journal of Energy and Power Engineering
SP  - 204
EP  - 208
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20130206.11
AB  - Computer based methods used to analysis the power systems are developed instead of the steady state of mathematical methods. By the development of computer technology, solution of the network problems gets easier. Increment of the necessity to electrical energy by the development of technology, whereas the increment rate of raw energy sources doesn’t enough, it have made it mandatory to use the energy sources efficiently. Interconnected networks formed by the connection between not only the domestic sources and customers, but also between the different countries for the optimization and for the efficient use of the sources. Electrical engineers faced by the planning and optimization problems of developing interconnected networks. By this way, the requirement of the use of intelligent systems and computer analysis of power systems has become inevitable. In this study, power flow analysis the of a power system that consist five busbars performed by designed neural network. Results are compared by the results that gained by the analysis with classic Gauss- Seidel method of the same system, then the success of the neural network is investigated.
VL  - 2
IS  - 6
ER  -

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Author Information

Serhat Berat EFE

Department of Electrical Engineering, F?rat University, Elaz??, Turkey
Mehmet CEBECİ

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APA Style

Serhat Berat EFE, Mehmet CEBECİ. (2013). Power Flow Analysis by Artificial Neural Network. International Journal of Energy and Power Engineering, 2(6), 204-208. https://doi.org/10.11648/j.ijepe.20130206.11

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ACS Style

Serhat Berat EFE; Mehmet CEBECİ. Power Flow Analysis by Artificial Neural Network. Int. J. Energy Power Eng. 2013, 2(6), 204-208. doi: 10.11648/j.ijepe.20130206.11

Copy | Download

AMA Style

Serhat Berat EFE, Mehmet CEBECİ. Power Flow Analysis by Artificial Neural Network. Int J Energy Power Eng. 2013;2(6):204-208. doi: 10.11648/j.ijepe.20130206.11

Copy | Download

@article{10.11648/j.ijepe.20130206.11,
  author = {Serhat Berat EFE and Mehmet CEBECİ},
  title = {Power Flow Analysis by Artificial Neural Network},
  journal = {International Journal of Energy and Power Engineering},
  volume = {2},
  number = {6},
  pages = {204-208},
  doi = {10.11648/j.ijepe.20130206.11},
  url = {https://doi.org/10.11648/j.ijepe.20130206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20130206.11},
  abstract = {Computer based methods used to analysis the power systems are developed instead of the steady state of mathematical methods. By the development of computer technology, solution of the network problems gets easier. Increment of the necessity to electrical energy by the development of technology, whereas the increment rate of raw energy sources doesn’t enough, it have made it mandatory to use the energy sources efficiently. Interconnected networks formed by the connection between not only the domestic sources and customers, but also between the different countries for the optimization and for the efficient use of the sources. Electrical engineers faced by the planning and optimization problems of developing interconnected networks. By this way, the requirement of the use of intelligent systems and computer analysis of power systems has become inevitable. In this study, power flow analysis the of a power system that consist five busbars performed by designed neural network. Results are compared by the results that gained by the analysis with classic Gauss- Seidel method of the same system, then the success of the neural network is investigated.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Power Flow Analysis by Artificial Neural Network
AU  - Serhat Berat EFE
AU  - Mehmet CEBECİ
Y1  - 2013/11/30
PY  - 2013
N1  - https://doi.org/10.11648/j.ijepe.20130206.11
DO  - 10.11648/j.ijepe.20130206.11
T2  - International Journal of Energy and Power Engineering
JF  - International Journal of Energy and Power Engineering
JO  - International Journal of Energy and Power Engineering
SP  - 204
EP  - 208
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20130206.11
AB  - Computer based methods used to analysis the power systems are developed instead of the steady state of mathematical methods. By the development of computer technology, solution of the network problems gets easier. Increment of the necessity to electrical energy by the development of technology, whereas the increment rate of raw energy sources doesn’t enough, it have made it mandatory to use the energy sources efficiently. Interconnected networks formed by the connection between not only the domestic sources and customers, but also between the different countries for the optimization and for the efficient use of the sources. Electrical engineers faced by the planning and optimization problems of developing interconnected networks. By this way, the requirement of the use of intelligent systems and computer analysis of power systems has become inevitable. In this study, power flow analysis the of a power system that consist five busbars performed by designed neural network. Results are compared by the results that gained by the analysis with classic Gauss- Seidel method of the same system, then the success of the neural network is investigated.
VL  - 2
IS  - 6
ER  -

Copy | Download