Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm

Mohammad Ali Hormozi; Mohammad Barghi Jahromi; Gholamreza Nasiri

doi:doi:10.11648/j.ijepe.20160505.11

| Peer-Reviewed

Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm

Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri

Published in International Journal of Energy and Power Engineering (Volume 5, Issue 5)

Received: 26 August 2016 Accepted: 13 September 2016 Published: 19 October 2016

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.

Published in	International Journal of Energy and Power Engineering (Volume 5, Issue 5)
DOI	10.11648/j.ijepe.20160505.11
Page(s)	163-170
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), 2016. Published by Science Publishing Group

Keywords

Distribution Network Reconfiguration, Distributed Generation, Hybrid Algorithm, Meta-Heuristic Algorithm, Binary Particular Swarm Optimization Algorithm, Power Loss

References

[1]	N. S. Rau and Y. H. Wan, “Optimal location of resources in distributed planning”, IEEE Trans. Power Syst., Vol. 9, pp. 2014-2020, Nov. 1994.
[2]	W. EI-hattam, M. M. A. Salma, “Distributed Generation Technologies, Definitions and Benefits” Elect. Power Syst. Res., Vol. 71, pp. 119-1283, 2004.
[3]	R. Srinivasa Rao, K. Ravindra, K. Satish, and S. V. L. Narasimham, “Power Loss Minimization in Distribution System Using Network Reconﬁguration in the Presence of Distributed Generation,” IEEE Trans. Power Syst., vol. 28, no. 1, pp. 317–325, Feb 2013.
[4]	C. Wang and M. H. Nehrir, “Analytical approaches for optimal placement of distributed generation sources in power systems,” IEEE Trans. Power Syst., vol. 19, no. 4, pp. 2068–2076, Nov. 2004.
[5]	G. Celli, E. Ghiani, S. Mocci, and F. Pilo, “A multi-objective evolutionary algorithm for the sizing and the sitting of distributed generation,” IEEE Trans. Power Syst., vol. 20, no. 2, pp. 750–757, May 2005.
[6]	J. J. Young, K. J. Chul, Jin-O. Kim, J. O. Joong-Rin Shin, K. Y. Lee, An efﬁcient simulated annealing algorithm for network reconﬁguration in large-scale distribution systems, IEEE Trans. Power Del., vol. 17, no. 4, pp. 1070–1078, October. 2002.
[7]	S. K. Goswami and S. K. Basu, “A new algorithm for the reconfiguration of distribution feeders for loss minimization,” IEEE Trans. Power Del., vol. 7, no. 3, pp. 1484–1491, July 1992.
[8]	A. Merlin and H. Back, “Search for a minimal-loss operating spanning tree configuration in an urban power distribution system,”in Proc. 5th Power System Computation Conf. (PSCC), Cambridge, U.K., pp. 1–18, 1975.
[9]	S. Civanlar, J. Grainger, H. Yin, and S. Lee, “Distribution feeder reconﬁguration for loss reduction,” IEEE Trans. Power Del., vol. 3, no. 3, pp. 1217–1223, Jul. 1988.
[10]	K. Nara, A. Shiose, M. Kitagawa, and T. Ishihara, “Implementation of genetic algorithm for distribution systems loss minimum reconfiguration,” IEEE Trans. Power Syst., vol. 7, no. 3, pp. 1044–1051, August 1992.
[11]	H. Kim, Y. Ko, and K. H. Jung, “Artificial neural networks based feeder reconfiguration for loss reduction in distribution systems,” IEEE Trans. Power Del., vol. 8, no. 3, pp. 1356–1366, July 1993.
[12]	H. C. Chang and C. C. Kuo, “Network reconfiguration in distribution system is using simulated annealing,” Elect. Power Syst. Res., vol. 29, pp. 227–238, May 1994.
[13]	J. Kennedy and R. Eberhart, “A discrete binary version of the particle swarm algorithm,” Proc. IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC 97), vol. 5, pp. 4104–4109, October 1997.
[14]	C. T. Su, C. F. Chang and J.-P. Chiou, “Distribution network reconfiguration for loss reduction by ant colony search algorithm,” Elect. Power Syst. Res., vol. 75, pp. 190–199, August 2005.
[15]	A. Mohamed Imran, M. Kowsalya, D. P. Kothari “A novel integration technique for optimal network reconﬁguration and distributed generation placement in power distribution network,” Electr Power Energy Syst., vol. 63, pp. 461–472, 2014
[16]	R. Srinivasa Rao, S. V. L. Narasimham, M. R. Raju, and A. Srinivasa Rao,“Optimal network reconﬁguration of large-scale distribution system using harmony search algorithm,” IEEE Trans. Power Syst., vol. 26, no. 3, pp. 1080–1088, Aug. 2011.
[17]	H. R. Esmaeilian, R. Fadaeinedjad, “Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation,” IEEE Syst. J., IEEE, pp. 1-10, July. 2014.
[18]	N. G. A. Hemdana, B. Deppec, M. Pielked, M. Kurrata, T. Schmedesd, E. Wiebene “Optimal reconfiguration of radial MV networks with load profiles in the presence of renewable energy based decentralized generation” Elect. Power Syst. Res., Vol. 116, pp. 355-366, November 2014.
[19]	M. E. Baran and F. Wu, “Network reconﬁguration in distribution system for loss reduction and load balancing,” IEEE Trans. Power Del., vol. 4, no. 2, pp. 1401–1407, Apr. 1989.
[20]	J. S. Savier and D. Das, “Impact of network reconﬁguration on loss allocation of radial distribution systems,” IEEE Trans. Power Del., vol. 2, no. 4, pp. 2473–2480, Oct. 2007.
[21]	J. Z. Zhu, “Optimal reconﬁguration of electrical distribution network using the reﬁned genetic algorithm,” Elect. Power Syst. Res., vol. 62, pp. 37–42, 2002.

Cite This Article

Plain Text BibTeX RIS

APA Style

Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri. (2016). Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. International Journal of Energy and Power Engineering, 5(5), 163-170. https://doi.org/10.11648/j.ijepe.20160505.11

Copy | Download

ACS Style

Mohammad Ali Hormozi; Mohammad Barghi Jahromi; Gholamreza Nasiri. Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. Int. J. Energy Power Eng. 2016, 5(5), 163-170. doi: 10.11648/j.ijepe.20160505.11

Copy | Download

AMA Style

Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri. Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. Int J Energy Power Eng. 2016;5(5):163-170. doi: 10.11648/j.ijepe.20160505.11

Copy | Download

@article{10.11648/j.ijepe.20160505.11,
  author = {Mohammad Ali Hormozi and Mohammad Barghi Jahromi and Gholamreza Nasiri},
  title = {Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm},
  journal = {International Journal of Energy and Power Engineering},
  volume = {5},
  number = {5},
  pages = {163-170},
  doi = {10.11648/j.ijepe.20160505.11},
  url = {https://doi.org/10.11648/j.ijepe.20160505.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20160505.11},
  abstract = {In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm
AU  - Mohammad Ali Hormozi
AU  - Mohammad Barghi Jahromi
AU  - Gholamreza Nasiri
Y1  - 2016/10/19
PY  - 2016
N1  - https://doi.org/10.11648/j.ijepe.20160505.11
DO  - 10.11648/j.ijepe.20160505.11
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  - 163
EP  - 170
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20160505.11
AB  - In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.
VL  - 5
IS  - 5
ER  -

Copy | Download

Author Information

Mohammad Ali Hormozi

Fars Regional Electrical Company, Shiraz, Iran
Mohammad Barghi Jahromi

Fars Regional Electrical Company, Shiraz, Iran
Gholamreza Nasiri

Fars Regional Electrical Company, Shiraz, Iran

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri. (2016). Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. International Journal of Energy and Power Engineering, 5(5), 163-170. https://doi.org/10.11648/j.ijepe.20160505.11

Copy | Download

ACS Style

Mohammad Ali Hormozi; Mohammad Barghi Jahromi; Gholamreza Nasiri. Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. Int. J. Energy Power Eng. 2016, 5(5), 163-170. doi: 10.11648/j.ijepe.20160505.11

Copy | Download

AMA Style

Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri. Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. Int J Energy Power Eng. 2016;5(5):163-170. doi: 10.11648/j.ijepe.20160505.11

Copy | Download

@article{10.11648/j.ijepe.20160505.11,
  author = {Mohammad Ali Hormozi and Mohammad Barghi Jahromi and Gholamreza Nasiri},
  title = {Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm},
  journal = {International Journal of Energy and Power Engineering},
  volume = {5},
  number = {5},
  pages = {163-170},
  doi = {10.11648/j.ijepe.20160505.11},
  url = {https://doi.org/10.11648/j.ijepe.20160505.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20160505.11},
  abstract = {In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm
AU  - Mohammad Ali Hormozi
AU  - Mohammad Barghi Jahromi
AU  - Gholamreza Nasiri
Y1  - 2016/10/19
PY  - 2016
N1  - https://doi.org/10.11648/j.ijepe.20160505.11
DO  - 10.11648/j.ijepe.20160505.11
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  - 163
EP  - 170
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20160505.11
AB  - In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.
VL  - 5
IS  - 5
ER  -

Copy | Download