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Reseach Article

Reliability Enhancement and Loss Reduction in Radial Distribution System by Reconfiguration using BFA

by E. R. Biju
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 41
Year of Publication: 2019
Authors: E. R. Biju
10.5120/ijca2019919294

E. R. Biju . Reliability Enhancement and Loss Reduction in Radial Distribution System by Reconfiguration using BFA. International Journal of Computer Applications. 178, 41 ( Aug 2019), 7-14. DOI=10.5120/ijca2019919294

@article{ 10.5120/ijca2019919294,
author = { E. R. Biju },
title = { Reliability Enhancement and Loss Reduction in Radial Distribution System by Reconfiguration using BFA },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2019 },
volume = { 178 },
number = { 41 },
month = { Aug },
year = { 2019 },
issn = { 0975-8887 },
pages = { 7-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number41/30807-2019919294/ },
doi = { 10.5120/ijca2019919294 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:52:46.011494+05:30
%A E. R. Biju
%T Reliability Enhancement and Loss Reduction in Radial Distribution System by Reconfiguration using BFA
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 41
%P 7-14
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a new methodology to solve radial distribution system (RDS) reconfiguration problem to reduce the losses and to enhance the reliability of the system. Optimal reconfiguration selects the best set of feeders by changing the switching status of sectionalizing and tie switches so that the resulting RDS has improved voltage profile and minimum power loss. In addition, the impact of DG and capacitor are also considered in the problem formulation. Also in order to calculate the reliability indices such as SAIFI, SAIDI, CAIDI, AENS and ASAI, the reconfiguration technique is considered as a failure rate reduction strategy. This paper presents the application of bacterial foraging algorithm (BFA) to solve optimal network reconfiguration problem. A standard IEEE 69 bus radial system is chosen for the study. To show the effectiveness of the proposed algorithm in finding the best solution, simulations are carried out on the test system and the results are briefly compared before and after reconfiguration.

References
  1. Mesut E. Baran and Felix F. Wu, 1989. “Network reconfiguration in distribution systems for loss reduction and load balancing”, IEEE Transactions on Power Delivery, Vol. 4, No. 2.
  2. T. Taylor and D. Lubkeman, 1990. “Implementation of heuristic search strategies for distribution feeder reconfiguration”, IEEE Transactions on Power Delivery, Vol.5, No.3, pp.239-245.
  3. D. Shirmohammadi and H. W. Hong, 1989. “Reconfiguration of electrical distribution networks for resistive line loss reduction”, IEEE Transactions on Power Systems, Vol. 4, No. 2, pp. 1492-1498.
  4. A. B. Morton and I. M. Y. Mareels,2000. “An efficient brute-force approach solution to the network reconfiguration problem”, IEEE Transactions on Power Delivery, Vol. 15, No. 3, pp. 996-1000.
  5. R. Srinivasa Rao, S. V. L. Narasimham, M. Ramalinga Raju, and A. Srinivasa Rao, 2011. “Optimal network reconfiguration of large-scale distribution system using harmony search algorithm”, IEEE Transactions on Power Systems, Vol. 26, No. 3, pp. 1080–1088.
  6. Y. T. Hsiao, 2004. “Mutiobjective evolution programming method for feeder reconfiguration”, IEEE Transactions on Power Systems, Vol. 19, No. 1, pp. 594-599.
  7. G. J. Peponis, M. P. Papadopulos and N. D. Hatziargyriou, 1996. “Optimal operation of distribution networks”, IEEE Transactions on Power Systems, Vol. 11, No. 1, pp. 59–67.
  8. C. F. Chang, 2008. “Reconfiguration and capacitor placement for loss reduction of distribution systems by ant colony search algorithm”, IEEE Transactions on Power Systems, Vol. 23, No.4, pp. 1747–1755.
  9. P. Rezaei and M. Vakilian, 2010. “Distribution system efficiency improvement by reconfiguration and capacitor placement using a modified particle swarm optimization algorithm”, IEEE Electrical Power and Energy Conference, Halifax, pp. 1–6.
  10. D. P. Montoya and J. M. Ramirez, 2012. “Reconfiguration and optimal capacitor placement for losses reduction”, IEEE/PES, Transmission and Distribution: Latin America Conference and Exposition, Montevideo, Piscataway, pp. 1–6.
  11. J. Dan and R. Baldick, 1996. “Optimal electric distribution system switch reconfiguration and capacitor control”, IEEE Transactions on Power Systems, Vol. 11, No.2, pp. 890–897.
  12. P. Rezaei, M. Vakilian and E. Hajipour, 2011. “Reconfiguration and capacitor placement in radial distribution systems for loss reduction and reliability enhancement”, 16th International Conference on Intelligent System Application to Power Systems, Hersonissos, Piscatawa, pp. 1–6.
  13. In-Su Bae and Jin-O Kim, 2007. “Reliability evaluation of distributed generation based on operation mode,” IEEE Transactions on Power Systems, Vol. 22, No. 2, pp. 785 -790.
  14. T. Gozel and M. H. Hocaoglu, 2009. “An analytical method for the sizing and siting of distributed generators in radial systems,” Electric Power Systems Research, Vol. 79, No. 6, pp. 912–918.
  15. B. Venkantesh, S. Chandramohan, N. Kanyavizhi and R. P. Kumudini Devi, 2009. “Optimal reconfiguration of radial distribution system using artificial intelligence methods” IEEE Toronto international conference, Toronto, ON, pp.660-665.
  16. M. R. Rashidi and M. F. Hajri, 2011. “Optimal planning of multiple distributed generation sources in distribution networks: A new approach”, Energy Conversion and Management, Vol. 52, No. 11, pp. 3301–3308.
  17. Q. Kang, T. Lan, Y. Yan, L. Wang and Q. Wu, 2012. “Group search optimizer based optimal location and capacity of distributed generations”, Journal Neurocomputing, Vol.78, No.1, pp.55–63.
  18. H. Hamedi and M. Gandomkar, 2012. “A straightforward approach to minimizing unsupplied energy and power loss through DG placement and evaluating power quality in relation to load variations over time”, Electrical Power and Energy Systems, Vol.35, No.1, pp. 93-96.
  19. L. Goel, R. Billinton, 1991. “Evaluation of interrupted energy assessment rates in distribution systems”, IEEE Transaction on Power Delivery, Vol. 6, No.4, pp.1876 –1882.
  20. R. Billinton, and R. N Allan, 1996. “Reliability evaluation of power systems”, Springer International Edition.
  21. B. Kevin and M. Passino, 2002. “Biomimicry of bacterial foraging for distributed optimization and control”, IEEE Control System Magazine, Vol. 22, No. 3, pp. 52– 67.
  22. Abdollah Kavousi-Fard and Taher Niknam, 2014. “Optimal distribution feeder reconfiguration for reliability improvement considering uncertainty”, IEEE Transaction on Power Delivery, Vol. 29, No. 3, pp. 1344-1353.
  23. Zahra Boor and Seyyed Mehdi Hosseini, 2013. “GA based optimal placement of DGs for loss reduction and reliability improvement in distribution networks with time varying loads”, International Journal of Intelligent Systems and Applications, Vol. 5, No. 4, pp. 55-63.
  24. Su Mon Myint and Soe Win Naing, 2015. “Network reconfiguration for loss reduction and voltage stability improvement of 74-bus radial distribution system using particle swarm optimization algorithm” International Journal of Electrical, Electronics and Data Communication, Vol. 3, No. 6, pp.32-38.
  25. M. Sedighizadeh M. Esmaili and M. M. Mahmoodi, 2017. “Reconfiguration of Distribution Systems to Improve Reliability and Reduce Power Losses using Imperialist Competitive Algorithm”, Iranian Journal of Electrical & Electronic Engineering, Vol. 13, No. 3, pp. 287-302.
  26. Arun Onlam, Daranpob Yodphet, Rongrit Chatthaworn, Chayada Surawanitkun, Apirat Siritaratiwat and Pirat Khunkitti, 2019. “Power Loss Minimization and Voltage Stability Improvement in Electrical Distribution System via Network Reconfiguration and Distributed Generation Placement Using Novel Adaptive Shuffled Frogs Leaping Algorithm www.mdpi.com/journal/energies, pp.4-12.
Index Terms

Computer Science
Information Sciences

Keywords

Distributed generator Reconfiguration Reliability indices Bacterial foraging algorithm Radial distribution system.