New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm

Arouna Oloulade; Adolphe Imano Moukengue; Richard Agbokpanzo; Antoine Vianou; Herman Tamadaho; Ramanou Badarou

doi:doi:10.11648/j.epes.20190805.13

| Peer-Reviewed

New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm

Arouna Oloulade, Adolphe Imano Moukengue, Richard Agbokpanzo, Antoine Vianou, Herman Tamadaho, Ramanou Badarou

Published in American Journal of Electrical Power and Energy Systems (Volume 8, Issue 5)

Received: 16 September 2019 Accepted: 8 October 2019 Published: 20 October 2019

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The losses in networks of Beninese Electrical Energy Company (SBEE) are very high and therefore constitute a concern for the operators. This work consisted in finding an optimal topology of a 41 nodes real network of SBEE by Modified Ant Colony Algorithms (MACA) in order to reduce the losses and ensure a continuous power supply to the customers in case of occurrence disturbances on any branch of this network. With technological breakthrough of Automation and Supervision Systems (SCADA), the operation of distribution networks can be ensured remotely in real time with the aim of minimizing losses, eliminating equipment overload and improving reliability. The criteria of technical performance improvement formulated under operating constraints are solved by Modified Ant Colony Algorithm (MACA) which is association of ant system and fuzzy logic on the Matlab platform. The best results obtained show the effectiveness and efficiency of this method. The SBEE's HVA networks can then be reconfigured automatically to significantly improve their continuity of supply and reliability. The improved results obtained after tests on a standard 33-nodes and a real 41 nodes networks show the robustness and accuracy of this MACA algorithm.

Published in	American Journal of Electrical Power and Energy Systems (Volume 8, Issue 5)
DOI	10.11648/j.epes.20190805.13
Page(s)	120-126
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), 2019. Published by Science Publishing Group

Keywords

Reconfiguration, Ant Colony Algorithm, Power Loss Reduction, Radial Distribution Network

References

[1]	H. K. Hazaa, H. H. Abdullah, M. H. Yasen, and S. S. Mustafa "Evaluation of electric energy losses in kirkuk distribution elecric system area", Iraqi J Electr Electron Eng, vol. 7, n° %12, pp. 144-150, 2011.
[2]	B. Gotzig, «Recherche du schéma optimal d'exploitation électrique,» PhD Thesis, Institut National Polytechnique de Grenoble, 1997.
[3]	A. Jain, A. R. Gupta, and A. Kumar, "An efficient method for D-STATCOM placement in radial distribution system", IEEE 6th India International Conference on Power Electronics (IICPE), pp. 1-6, 2014.
[4]	DD/SBEE, «Rapport d'analyse des incidents sur le réseau HTA (Période de Juillet à Septembre),» oct. 2017.
[5]	A. Merlin, «"Search for minimal-loss operating spanning tree configuration for an urban power distribution system",» Proc 5th PSCC, vol. 1, pp. 1-18, 1975.
[6]	J. Li, "Reconfiguration of power networks based on graph-the-oretic algorithm", 2010.
[7]	V. Tudor, "Optimal loss Reduction of distribution networks using a refined genetic algorithm", Sci. Bull. C Electr. Eng., vol. 72, n° %13, pp. 29-38, 2010.
[8]	Nagy S. A. and I. S. IBRAHIM., "Network Reconfiguration for Loss Reduction in Electrical Distribution System Using Genetic Algorithm", Arab Journal of Nuclear Science and Applications, India Journal of Science and Technology, vol. 46, pp. 78-87, 2013.
[9]	Vizhiy S. ARUUL, Santhi R. K. and Nachiappan ALAMELU, "Biogeography based Optimization for Multi-Objective Reconfiguration Problem in Distribution Networks", Indian Journal of Science and Technology, n° 19, pp. 48-52, 2016.
[10]	Tamer M. KHALIL SELIM, Alexander GORPINICH and Irena WASIAK, “A selective particle swarm optimization for large scale practical distribution system reconfiguration", June 2015.
[11]	Tung TRAN, «"Distribution Network Reconfiguration Using One RankCucckoo Search Algorithm",» GMSARN International Journal, vol. 9, n° %111, 2016.
[12]	Abhiraj T. K and P. Aravindhababu, "Dragonfly Optimization based Reconfiguration for Voltage Profile Enhancement in Distribution Systems", International Journal of Computer Application, vol. 158, n° %12, pp. 48-52, 2017.
[13]	Abrar TANJUNG, "Reconfiguration of Power Supply System Distribution 20 kV PT PLN (Persero) Dumai Area Case", JOP Conference Series: Earth and Environmental Science, n° %1175, juil 2017.
[14]	D. Shirmohammadi and H. W. Hong, "Reconfiguration of distribution networks for resistive line losses reduction", IEEE Trans. Power Deliv, vol. 4, n° %12, pp. 1492-1498, 1989.
[15]	A. Oloulade, A. Moukengue Imano, A. Vianou, and H. Tamadaho,"Optimization of the number, size and placement of D-STATCOM in radial distribution network using Ant Colony Algorithm", 2018.
[16]	H. B. Tolabi, M. H. Ali, and M. Rizwan, "Simultaneous reconfiguration optimal placement of D-STATCOM and photovolaic array in a distribution system based on fuzzy-ACO approch", IEEE Trans Sustain Energy, vol. 6, n° %11, pp. 210-218, 2015.
[17]	A. Oloulade, A. Moukengue Imano, A. Vianou, and H. Tamadaho, "Optimzation multi-critère du placement d'un D-STATCOM dans un réseau de distribution par les Colonies de Fourmis", 2018.
[18]	R. K. Jacob et V. Malathi, "Optimization Reconfiguration of Power Distribution Systems", 2015.
[19]	R. Srinivasa Rao, "Optimization of Distribution Network Configuration for Loss Reduction Using Artificial Bee Colony Algorithm", International Journal of Electrical and Computer Engineering, vol. 2, n° %19, 2008.

Cite This Article

Plain Text BibTeX RIS

APA Style

Arouna Oloulade, Adolphe Imano Moukengue, Richard Agbokpanzo, Antoine Vianou, Herman Tamadaho, et al. (2019). New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm. American Journal of Electrical Power and Energy Systems, 8(5), 120-126. https://doi.org/10.11648/j.epes.20190805.13

Copy | Download

ACS Style

Arouna Oloulade; Adolphe Imano Moukengue; Richard Agbokpanzo; Antoine Vianou; Herman Tamadaho, et al. New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm. Am. J. Electr. Power Energy Syst. 2019, 8(5), 120-126. doi: 10.11648/j.epes.20190805.13

Copy | Download

AMA Style

Arouna Oloulade, Adolphe Imano Moukengue, Richard Agbokpanzo, Antoine Vianou, Herman Tamadaho, et al. New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm. Am J Electr Power Energy Syst. 2019;8(5):120-126. doi: 10.11648/j.epes.20190805.13

Copy | Download

@article{10.11648/j.epes.20190805.13,
  author = {Arouna Oloulade and Adolphe Imano Moukengue and Richard Agbokpanzo and Antoine Vianou and Herman Tamadaho and Ramanou Badarou},
  title = {New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {8},
  number = {5},
  pages = {120-126},
  doi = {10.11648/j.epes.20190805.13},
  url = {https://doi.org/10.11648/j.epes.20190805.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20190805.13},
  abstract = {The losses in networks of Beninese Electrical Energy Company (SBEE) are very high and therefore constitute a concern for the operators. This work consisted in finding an optimal topology of a 41 nodes real network of SBEE by Modified Ant Colony Algorithms (MACA) in order to reduce the losses and ensure a continuous power supply to the customers in case of occurrence disturbances on any branch of this network. With technological breakthrough of Automation and Supervision Systems (SCADA), the operation of distribution networks can be ensured remotely in real time with the aim of minimizing losses, eliminating equipment overload and improving reliability. The criteria of technical performance improvement formulated under operating constraints are solved by Modified Ant Colony Algorithm (MACA) which is association of ant system and fuzzy logic on the Matlab platform. The best results obtained show the effectiveness and efficiency of this method. The SBEE's HVA networks can then be reconfigured automatically to significantly improve their continuity of supply and reliability. The improved results obtained after tests on a standard 33-nodes and a real 41 nodes networks show the robustness and accuracy of this MACA algorithm.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm
AU  - Arouna Oloulade
AU  - Adolphe Imano Moukengue
AU  - Richard Agbokpanzo
AU  - Antoine Vianou
AU  - Herman Tamadaho
AU  - Ramanou Badarou
Y1  - 2019/10/20
PY  - 2019
N1  - https://doi.org/10.11648/j.epes.20190805.13
DO  - 10.11648/j.epes.20190805.13
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 120
EP  - 126
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20190805.13
AB  - The losses in networks of Beninese Electrical Energy Company (SBEE) are very high and therefore constitute a concern for the operators. This work consisted in finding an optimal topology of a 41 nodes real network of SBEE by Modified Ant Colony Algorithms (MACA) in order to reduce the losses and ensure a continuous power supply to the customers in case of occurrence disturbances on any branch of this network. With technological breakthrough of Automation and Supervision Systems (SCADA), the operation of distribution networks can be ensured remotely in real time with the aim of minimizing losses, eliminating equipment overload and improving reliability. The criteria of technical performance improvement formulated under operating constraints are solved by Modified Ant Colony Algorithm (MACA) which is association of ant system and fuzzy logic on the Matlab platform. The best results obtained show the effectiveness and efficiency of this method. The SBEE's HVA networks can then be reconfigured automatically to significantly improve their continuity of supply and reliability. The improved results obtained after tests on a standard 33-nodes and a real 41 nodes networks show the robustness and accuracy of this MACA algorithm.
VL  - 8
IS  - 5
ER  -

Copy | Download

Author Information

Arouna Oloulade

Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin
Adolphe Imano Moukengue

Electronic, Electrotechnic, Automatic, Telecommunications Laboratory (LEEAT), University of Douala, Douala, Cameroun
Richard Agbokpanzo

Polytechnic School of Abomey-Calavi, University of Abomey-Calavi, Abomey-Calavi, Benin
Antoine Vianou

Laboratory of Thermophysic Characterization of Materials and Energy Mastering, University of Abomey-Calavi, Cotonou, Benin
Herman Tamadaho

Electrotechnic, Telecommunications and Informatics Laboratory (LETIA), University of Abomey-Calavi, Abomey-Calavi, Benin
Ramanou Badarou

Polytechnic School of Abomey-Calavi, University of Abomey-Calavi, Abomey-Calavi, Benin

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Arouna Oloulade, Adolphe Imano Moukengue, Richard Agbokpanzo, Antoine Vianou, Herman Tamadaho, et al. (2019). New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm. American Journal of Electrical Power and Energy Systems, 8(5), 120-126. https://doi.org/10.11648/j.epes.20190805.13

Copy | Download

ACS Style

Arouna Oloulade; Adolphe Imano Moukengue; Richard Agbokpanzo; Antoine Vianou; Herman Tamadaho, et al. New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm. Am. J. Electr. Power Energy Syst. 2019, 8(5), 120-126. doi: 10.11648/j.epes.20190805.13

Copy | Download

AMA Style

Arouna Oloulade, Adolphe Imano Moukengue, Richard Agbokpanzo, Antoine Vianou, Herman Tamadaho, et al. New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm. Am J Electr Power Energy Syst. 2019;8(5):120-126. doi: 10.11648/j.epes.20190805.13

Copy | Download

@article{10.11648/j.epes.20190805.13,
  author = {Arouna Oloulade and Adolphe Imano Moukengue and Richard Agbokpanzo and Antoine Vianou and Herman Tamadaho and Ramanou Badarou},
  title = {New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {8},
  number = {5},
  pages = {120-126},
  doi = {10.11648/j.epes.20190805.13},
  url = {https://doi.org/10.11648/j.epes.20190805.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20190805.13},
  abstract = {The losses in networks of Beninese Electrical Energy Company (SBEE) are very high and therefore constitute a concern for the operators. This work consisted in finding an optimal topology of a 41 nodes real network of SBEE by Modified Ant Colony Algorithms (MACA) in order to reduce the losses and ensure a continuous power supply to the customers in case of occurrence disturbances on any branch of this network. With technological breakthrough of Automation and Supervision Systems (SCADA), the operation of distribution networks can be ensured remotely in real time with the aim of minimizing losses, eliminating equipment overload and improving reliability. The criteria of technical performance improvement formulated under operating constraints are solved by Modified Ant Colony Algorithm (MACA) which is association of ant system and fuzzy logic on the Matlab platform. The best results obtained show the effectiveness and efficiency of this method. The SBEE's HVA networks can then be reconfigured automatically to significantly improve their continuity of supply and reliability. The improved results obtained after tests on a standard 33-nodes and a real 41 nodes networks show the robustness and accuracy of this MACA algorithm.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - New Multi Objective Approach for Optimal Network Reconfiguration in Electrical Distribution Systems Using Modified Ant Colony Algorithm
AU  - Arouna Oloulade
AU  - Adolphe Imano Moukengue
AU  - Richard Agbokpanzo
AU  - Antoine Vianou
AU  - Herman Tamadaho
AU  - Ramanou Badarou
Y1  - 2019/10/20
PY  - 2019
N1  - https://doi.org/10.11648/j.epes.20190805.13
DO  - 10.11648/j.epes.20190805.13
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 120
EP  - 126
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20190805.13
AB  - The losses in networks of Beninese Electrical Energy Company (SBEE) are very high and therefore constitute a concern for the operators. This work consisted in finding an optimal topology of a 41 nodes real network of SBEE by Modified Ant Colony Algorithms (MACA) in order to reduce the losses and ensure a continuous power supply to the customers in case of occurrence disturbances on any branch of this network. With technological breakthrough of Automation and Supervision Systems (SCADA), the operation of distribution networks can be ensured remotely in real time with the aim of minimizing losses, eliminating equipment overload and improving reliability. The criteria of technical performance improvement formulated under operating constraints are solved by Modified Ant Colony Algorithm (MACA) which is association of ant system and fuzzy logic on the Matlab platform. The best results obtained show the effectiveness and efficiency of this method. The SBEE's HVA networks can then be reconfigured automatically to significantly improve their continuity of supply and reliability. The improved results obtained after tests on a standard 33-nodes and a real 41 nodes networks show the robustness and accuracy of this MACA algorithm.
VL  - 8
IS  - 5
ER  -

Copy | Download