BPSO Applied to TNEP Considering Adequacy Criterion

Meisam Mahdavi; Amir Bagheri

doi:doi:10.11648/j.ajnna.20180401.11

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BPSO Applied to TNEP Considering Adequacy Criterion

Meisam Mahdavi, Amir Bagheri

Published in American Journal of Neural Networks and Applications (Volume 4, Issue 1)

Received: 10 November 2017 Accepted: 19 January 2018 Published: 30 January 2018

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Abstract

Different methods have been proposed to solve the static transmission network expansion planning (STNEP) problem up to now. But in all of these studies, loading of transmission lines has not been studied using binary particle swarm optimization (BPSO) algorithm. BPSO is a good optimization method to solve nonlinear large-scale problems with discrete variables like STNEP. Thus, in this paper, STNEP problem is being studied considering network adequacy criterion using BPSO. The goal of this paper is obtaining a configuration for network expansion with lowest expansion cost and a specific adequacy. The proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.

Published in	American Journal of Neural Networks and Applications (Volume 4, Issue 1)
DOI	10.11648/j.ajnna.20180401.11
Page(s)	1-7
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), 2018. Published by Science Publishing Group

Keywords

BPSO, Adequacy Criterion, STNEP

References

[1]	M. Mahdavi, H. Monsef, R. Romero “Reliability and economic effects of maintenance on TNEP considering line loading and repair” IEEE Transactions on Power Systems, vol. 31, no. 5, pp.3381–3393, 2016.
[2]	M. Mahdavi, H. Monsef, R. Romero “Reliability effects of maintenance on TNEP considering preventive and corrective repairs” IEEE Transactions on Power Systems, vol. 32, no. 5, pp.3768–3781, 2017.
[3]	M. Mahdavi, E. Mahdavi “Transmission expansion planning considering network adequacy and investment cost limitation using genetic algorithm” World Academy of Science, Engineering and Technology, vol. 5, no. 8, pp: 1–5, 2011.
[4]	A. Kazemi, S. Jalilzadeh, M. Mahdavi, H. Haddadian “Genetic algorithm-based investigation of load growth factor effect on the network loss in TNEP” 3rd IEEE Conference on Industrial Electronics and Applications, Singapore, vol. 1, pp. 764–769, June 2008.
[5]	M. Mahdavi, H. Monsef, A. Bagheri “Dynamic transmission network expansion planning considering network losses, DG sources and operational costs-part 1: review and problem formulation” WULFENIA, vol. 19, no. 10, pp. 242–257, 2012.
[6]	H. Shayeghi, M. Mahdavi “Application of PSO and GA for transmission network expansion planning” Book chapter in: Analysis, control and optimal operations in hybrid power systems, London, Springer, 2013, pp. 187–226.
[7]	M. Mahdavi, H. Monsef “Review of static transmission expansion planning” Journal of Electrical and Control Engineering, vol. 1, no. 1, pp. 11–18, 2011.
[8]	M. Mahdavi, A. Bagheri, E. Mahdavi “Comparing efficiency of PSO with GA in transmission expansion planning considering network adequacy” WSEAS Transactions on Power Systems, vol. 7, no. 1, pp. 34–43, 2012.
[9]	H. Shayeghi, M. Mahdavi, H. Haddadian “DCGA based-transmission network expansion planning considering network adequacy” International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 2, no. 12, pp. 2875–2880, 2008.
[10]	J. Contreras, F. F. Wu “A kernel-oriented algorithm for transmission expansion planning” IEEE Transactions on Power Systems, vol. 15, no. 4, pp. 1434–1440.
[11]	S. Jalilzadeh, A. Kimiyaghalam, M. Mahdavi, A. Ashouri “STNEP considering voltage level and uncertainty in demand using IABPSO” International Review of Electrical Engineering, vol. 7, no. 4, pp. 5186–5195, 2012.
[12]	R. A. Gallego, R. Romero, A. J. Monticelli “Tabu search algorithm for network synthesis” IEEE Transactions on Power Systems, vol. 15, no. 2, pp. 490–495, 2000.
[13]	A. Kimiyaghalam, M. Mahdavi, S. Jalilzadeh, A. Ashouri “Improved binary particle swarm optimization based TNEP considering network losses, voltage level, and uncertainty in demand” Journal of Artificial Intelligence in Electrical Engineering, vol. 1, no. 2, pp. 29–42, 2012.
[14]	H. Shayeghi, M. Mahdavi, A. Bagheri “An improved DPSO with mutation based on similarity algorithm for optimization of transmission lines loading” Energy Conversion and Management, vol. 51, no. 12, pp. 2715–2723, 2010.
[15]	R. Romero, R. A. Gallego, A. Monticelli “Transmission system expansion planning by simulated annealing” IEEE Transactions on Power Systems, vol. 11, no. 1, pp. 364–369, 1996.
[16]	R. Romero, A. Monticelli “A hierarchical decomposition approach for transmission network expansion planning” IEEE Transactions on Power Systems, vol. 9, no. 1, pp. 373–380, 1994.
[17]	S. Binato, G. C. de Oliveira, J. L. Araujo “A greedy randomized adaptive search procedure for transmission expansion planning” IEEE Transactions on Power Systems, vol. 16, no. 2, pp. 247–253, 2001.
[18]	T. Al-Saba, I. El-Amin “The application of artificial intelligent tools to the transmission expansion problem” Electric Power Systems Research, vol. 62, no. 2, pp. 117–126, 2002.
[19]	R. C. G. Teive, E. L. Silva, L. G. S. Fonseca “A cooperative expert system for transmission expansion planning of electrical power systems” IEEE Transactions on Power Systems, vol. 13, no. 2, pp. 636–642, 1998;13(2):.
[20]	S. Binato, M. V. F. Periera, S. Granville “A new Benders decomposition approach to solve power transmission network design Problems” IEEE Transactions on Power Systems, vol. 16, no. 2, pp. 235–240, 2001.
[21]	M. V. F. Periera, L. M. V. G. Pinto “Application of sensitivity analysis of load supplying capacity to interactive transmission expansion planning” IEEE Transactions on Power Apparatus and Systems, vol. PAS-104, pp. 381–389, 1985.
[22]	R. A. Gallego, A. B. Alves, A. Monticelli, R. Romero “Parallel simulated annealing applied to long term transmission network expansion planning” IEEE Transactions on Power Systems, vol. 12, no. 1, pp. 181–188, 1997.
[23]	A. M. L. Silva, L. S. Rezende, L. A. F. Manso, L. C. Resende “Reliability worth applied to transmission expansion planning based on ant colony system” International Journal of Electrical Power & Energy Systems, vol. 32, pp. 1077–1084, 2010.
[24]	M. Khodayari, M. Mahdavi, H. Monsef “Simultaneous scheduling of energy & spinning reserve considering customer and supplier choice on reliability” 19th Iranian Conference on Electrical Engineering, Iran, pp. 491–496, May 2011.
[25]	H. Shayeghi, M. Mahdavi “Studying the effect of losses coefficient on transmission expansion planning using decimal codification based GA” International Journal on Technical and Physical Problems of Engineering, vol. 1, no. 1, pp. 58–64, 2009.
[26]	H. Shayeghi, M. Mahdavi “Optimization of transmission lines loading in TNEP using decimal codification based GA” International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 2, no. 2, pp.1–18, 2008.
[27]	H. Shayeghi, S. Jalilzadeh, M. Mahdavi, H. Hadadian “Role of voltage level and network losses in TNEP solution” Journal of Electrical Systems, vol. 5, no. 3, pp.1–18, 2009.
[28]	H. Shayeghi, H. Hosseini, A. Shabani, M. Mahdavi “GEP considering purchase prices, profits of IPPs and reliability criteria using hybrid GA and PSO” International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 2, no. 12, pp. 2875–2880, 2008.
[29]	M. Mahdavi, H. Monsef, A. Bagheri “Dynamic transmission network expansion planning considering network losses, DG sources and operational costs-part 2: solution method and numerical results” WULFENIA, vol. 19, no. 10, pp. 258–273, 2012.
[30]	J. Aghaei, N. Amjady, A. Baharvandi, M. A.. Akbari “Generation and transmission expansion planning: MILP-based probabilistic model” IEEE Transactions on Power Systems, vol. 49, pp. 1592–1601, 2014.
[31]	A. S. D. Braga, J. T. Saraiva “A multiyear dynamic approach for transmission expansion planning and long-term marginal costs computation” IEEE Transactions on Power Systems, vol. 20, no. 3, pp. 1631–1639, 2005.
[32]	H. Shayeghi, M. Mahdavi, A. Kazemi, H. A. Shayanfar “Studying effect of bundle lines on TNEP considering network losses using decimal codification genetic algorithm” Energy Conversion and Management, vol. 51, no. 12, pp. 2685–2691, 2010.
[33]	H. Shayeghi, M. Mahdavi “Genetic algorithm based studying of bundle lines effect on network losses in transmission network expansion planning” Journal of Electrical Engineering, vol. 60, no. 5, pp. 237–245, 2009.
[34]	V. Rashtchi, H. Shayeghi, M. Mahdavi, A. Kimiyaghalam, E. Rahimpour, “Using an improved PSO algorithm for parameter identification of transformer detailed model” International Journal of Electrical Power and Energy Systems Engineering, vol. 1, no. 3, pp. 138–144, 2008.
[35]	H. Shayeghi, M. Mahdavi, A. Kazemi “Discrete particle swarm optimization algorithm used for TNEP considering network adequacy restriction” International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 3, no. 3, pp. 521–528, 2009.
[36]	S. Jalilzadeh, A. Kazemi, M. Mahdavi, H. Haddadian “TNEP considering voltage level, network losses and number of bundle lines using GA” Third International Conference on Electric Utility, Deregulation, Restructuring and Power Technologies, pp. 1580–1585, April 2008.
[37]	M. Mahdavi, S. Jalilzadeh “Advanced particle swarm optimization for parameter identification of three-phase DFIM” The 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, China, pp. 580–584, November 2009.
[38]	M. Mahdavi, H. Monsef “Advanced particle swarm optimization used for optimal design of single-phase induction motor” International Journal on Technical and Physical Problems of Engineering, vol. 1, no. 1, pp. 55–59, 2010.
[39]	M. Mahdavi, E. Mahdavi “Evaluating the effect of load growth on annual network losses in TNEP considering bundle lines using DCGA” International Journal on Technical and Physical Problems of Engineering, vol. 3, no. 4, pp. 1–9, 2011.
[40]	M. Mahdavi, H. Monsef, A. Bagheri “Transmission lines loading enhancement using ADPSO approach” International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 4, no. 3, pp. 556–561, 2010.
[41]	N. Jin, Y. R. Samii “Advances in particle swarm optimization for antenna designs: real-number, binary, single-objective and multiobjective implementations” IEEE Transactions on Antennas and Propagation, vol. 55, no. 3, pp. 556–567, 2007.

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APA Style

Meisam Mahdavi, Amir Bagheri. (2018). BPSO Applied to TNEP Considering Adequacy Criterion. American Journal of Neural Networks and Applications, 4(1), 1-7. https://doi.org/10.11648/j.ajnna.20180401.11

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ACS Style

Meisam Mahdavi; Amir Bagheri. BPSO Applied to TNEP Considering Adequacy Criterion. Am. J. Neural Netw. Appl. 2018, 4(1), 1-7. doi: 10.11648/j.ajnna.20180401.11

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AMA Style

Meisam Mahdavi, Amir Bagheri. BPSO Applied to TNEP Considering Adequacy Criterion. Am J Neural Netw Appl. 2018;4(1):1-7. doi: 10.11648/j.ajnna.20180401.11

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@article{10.11648/j.ajnna.20180401.11,
  author = {Meisam Mahdavi and Amir Bagheri},
  title = {BPSO Applied to TNEP Considering Adequacy Criterion},
  journal = {American Journal of Neural Networks and Applications},
  volume = {4},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.ajnna.20180401.11},
  url = {https://doi.org/10.11648/j.ajnna.20180401.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20180401.11},
  abstract = {Different methods have been proposed to solve the static transmission network expansion planning (STNEP) problem up to now. But in all of these studies, loading of transmission lines has not been studied using binary particle swarm optimization (BPSO) algorithm. BPSO is a good optimization method to solve nonlinear large-scale problems with discrete variables like STNEP. Thus, in this paper, STNEP problem is being studied considering network adequacy criterion using BPSO. The goal of this paper is obtaining a configuration for network expansion with lowest expansion cost and a specific adequacy. The proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.},
 year = {2018}
}

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TY  - JOUR
T1  - BPSO Applied to TNEP Considering Adequacy Criterion
AU  - Meisam Mahdavi
AU  - Amir Bagheri
Y1  - 2018/01/30
PY  - 2018
N1  - https://doi.org/10.11648/j.ajnna.20180401.11
DO  - 10.11648/j.ajnna.20180401.11
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20180401.11
AB  - Different methods have been proposed to solve the static transmission network expansion planning (STNEP) problem up to now. But in all of these studies, loading of transmission lines has not been studied using binary particle swarm optimization (BPSO) algorithm. BPSO is a good optimization method to solve nonlinear large-scale problems with discrete variables like STNEP. Thus, in this paper, STNEP problem is being studied considering network adequacy criterion using BPSO. The goal of this paper is obtaining a configuration for network expansion with lowest expansion cost and a specific adequacy. The proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.
VL  - 4
IS  - 1
ER  -

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Author Information

Meisam Mahdavi

Department of Electrical Engineering, S?o Paulo State University, Ilha Solteira, Brazil
Amir Bagheri

Department of Electrical Engineering, University of Zanjan, Zanjan, Iran

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APA Style

Meisam Mahdavi, Amir Bagheri. (2018). BPSO Applied to TNEP Considering Adequacy Criterion. American Journal of Neural Networks and Applications, 4(1), 1-7. https://doi.org/10.11648/j.ajnna.20180401.11

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ACS Style

Meisam Mahdavi; Amir Bagheri. BPSO Applied to TNEP Considering Adequacy Criterion. Am. J. Neural Netw. Appl. 2018, 4(1), 1-7. doi: 10.11648/j.ajnna.20180401.11

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AMA Style

Meisam Mahdavi, Amir Bagheri. BPSO Applied to TNEP Considering Adequacy Criterion. Am J Neural Netw Appl. 2018;4(1):1-7. doi: 10.11648/j.ajnna.20180401.11

Copy | Download

@article{10.11648/j.ajnna.20180401.11,
  author = {Meisam Mahdavi and Amir Bagheri},
  title = {BPSO Applied to TNEP Considering Adequacy Criterion},
  journal = {American Journal of Neural Networks and Applications},
  volume = {4},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.ajnna.20180401.11},
  url = {https://doi.org/10.11648/j.ajnna.20180401.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20180401.11},
  abstract = {Different methods have been proposed to solve the static transmission network expansion planning (STNEP) problem up to now. But in all of these studies, loading of transmission lines has not been studied using binary particle swarm optimization (BPSO) algorithm. BPSO is a good optimization method to solve nonlinear large-scale problems with discrete variables like STNEP. Thus, in this paper, STNEP problem is being studied considering network adequacy criterion using BPSO. The goal of this paper is obtaining a configuration for network expansion with lowest expansion cost and a specific adequacy. The proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - BPSO Applied to TNEP Considering Adequacy Criterion
AU  - Meisam Mahdavi
AU  - Amir Bagheri
Y1  - 2018/01/30
PY  - 2018
N1  - https://doi.org/10.11648/j.ajnna.20180401.11
DO  - 10.11648/j.ajnna.20180401.11
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20180401.11
AB  - Different methods have been proposed to solve the static transmission network expansion planning (STNEP) problem up to now. But in all of these studies, loading of transmission lines has not been studied using binary particle swarm optimization (BPSO) algorithm. BPSO is a good optimization method to solve nonlinear large-scale problems with discrete variables like STNEP. Thus, in this paper, STNEP problem is being studied considering network adequacy criterion using BPSO. The goal of this paper is obtaining a configuration for network expansion with lowest expansion cost and a specific adequacy. The proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.
VL  - 4
IS  - 1
ER  -

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