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Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm

by Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 3
Year of Publication: 2013
Authors: Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri
10.5120/10611-5327

Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri . Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm. International Journal of Computer Applications. 64, 3 ( February 2013), 1-10. DOI=10.5120/10611-5327

@article{ 10.5120/10611-5327,
author = { Rajneesh K. Karn, Yogendra Kumar, Gayatri Agnihotri },
title = { Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 3 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number3/10611-5327/ },
doi = { 10.5120/10611-5327 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:15:24.802886+05:30
%A Rajneesh K. Karn
%A Yogendra Kumar
%A Gayatri Agnihotri
%T Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 3
%P 1-10
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To restore electricity service in healthy area outside the faulted zone in power distribution system is known as service restoration. In this paper, a technique based on hybrid Genetic Algorithm-Ant Colony Optimization (GA-ACO) is presented for solving the service restoration problem in electric power distribution system. Due the presence of various conflicting objectives and constraints, the task of service restoration is multi-objective and multi-constraint optimization problem. In contrast to conventional optimization technique, this approach does not require tunable weighting factors to convert multiple objectives into equivalent single objective. In this work various practical distribution systems issues such as presence of priority customers, remotely and manually controlled switches etc have been considered as objective functions. Based on simulation results on four different distribution networks, the performance of hybrid GA-ACO is found significantly better than Non Dominated Sorting of Genetic Algorithm-II (NSGA-II) and conventional Genetic Algorithm.

References
  1. Akoi, H. Kuwabara T. Satoh M. Kanezashi, "Outage state optimal load allocation by automatic sectionalizing switches operation in distribution systems," IEEE trans. Power delivery. 1987,vol. 2, no. 4, pp. 1177-1185
  2. K. Akoi , H. Kuwabara T. Satoh M. Kanezashi, "Voltage drop constrained restoration of supply by switch operation in distribution system," IEEE trans. Power delivery. 1988 vol. 3, no. 3, pp. 1267-1279.
  3. K. Akoi, H. Kuwabara T. Satoh M. Kanezashi, "A new algorithm for service restoration in distribution systems," IEEE trans. Power delivery. 1989 vol. 4, no. 3, pp. 1832-1839.
  4. C. C. liu S. J. Lee, S. S. Venkata "An expert system operational aid for restoration and loss reduction of distribution systems," IEEE trans. Power syst. 1988 vol. 3, no. 2, pp. 619-626
  5. C. E. Lin et al. , "A distribution system outage dispatch by data base method with real time revision," IEEE trans. Power Delivery, vol. 4. Jan. 1989.
  6. Imamura et al. , "An application of fuzzy reasoning for service restoration" (in Japanese) Trans. IEE Jpn. , vol. 4, July 1989.
  7. H. Mori et al. , Parallel simulated annealing for power system decomposition," IEEE trans. Power system vol. 4, May 1994.
  8. S. Toune, H. Fudo, T. Genji, Y. Fukuyama, Y. Nakanishi, "A reactive tabu search for service restoration in electric power distribution system," IEEE International conference on evolutionary computation," Anchorage Alaska, May 4-11 1998.
  9. H. C. Kuo and Y. Y Hsu, " Distribution system load estimation and service restoration using a fuzzy set approach", IEEE Transactions on Power delivery, Vol-8, No-4, pp-1950-1957, Oct. 1993
  10. S. J. Lee, S. I. Lim, and B. S. Ahn, " Service restoration of primary distribution system based on fuzzy evaluation of multi criteria", IEEE Transactions on Power System, Vol-13, No-3, pp-1156-1163, Aug. 1998
  11. Y. Fukuyama and H. D. chaing, "A parallel genetic algorithm for service restoration in electric power systems," in proceeding IEEE FUZZ/FES Conference, Yokohama, Japan, Mar. 1995.
  12. A. Augugliaro, L. Dusonchet, E. R. Sanseverino, "Service restoration in compensated distribution networks using a hybrid genetic algorithm," Electric power syst. Research, 1998, vol. 46, 59-66.
  13. W. P. Luan, M. R. Irving, J. S. Daniel, "Genetic algorithm for supply restoration and optimal load shedding in power system distribution networks," IEE Proc. Gener. Transm. Distrib. , 2002, vol. 149, no. 2, pp. 145-15 1.
  14. Y. T. Hsiao and C. Y. Chien, "Enhancement of restoration service in distribution systems using a combination of fuzzy-GA method," IEEE
  15. Yogendra Kumar, Biswarup Das, Jaydev Sharma, Genetic Algorithm for supply restoration in distribution system with priority customers 9th international Conference on Probabilistic Methods applied to power systems , Sweden, June 2006.
  16. R. E. Brown, S. Gupta, R. D. Christie and S. S. Venkata, "A genetic algorithm for reliable distribution system design", International Conference on Intelligent Systems Applications to Power Systems, ISAP '96. , pp. 29-33, January 28 - February 2,1996.
  17. S. Chavali, A. Pahwa and S. Das, "A genetic algorithm approach for optimal distribution feeder restoration during cold load pickup", Proceedings of the Congress on Evolutionary Computation, CEC '02, vol. 2, pp. 1816-1819, May 12-17, 2002.
  18. Y. Kumar, B. Das and J. Sharma, " Multiobjective, multiconstraint service restoration of electric power distribution system with priority customers", IEEE Transactions on Power delivery, Vol-23, No-1, pp-261-270, Jan. 2008
  19. Jen-Hao Teng,Yi-Hwa Liu, "Application of the Ant Colony System for Optimum switch adjustment", IEEE Transactions on power Systems,Vol. 17,No. 1,pp. 751-756,2002
  20. Jen-Hao Teng,Yi-Hwa Liu, " A Novel ACS-Based optimum Switch Relocation Method" IEEE Transactions on power systems,Vol. 18,No. 1,pp. 113-120,2003.
  21. Indira Mohanty,Jugal Kalita,Sanjoy Das,Anil Pahwa,Erik Buehler, "Ant Algorithm for the optimal restoration of Distribution feeders during cold load pickup',IEEE Transactions on Power Delivery,pp. 132-137,2003.
  22. Isamu Watanabe, "An ACO Algorithm for service Restoration in Power Distribution Systems", IEEE Transactions on Power delivery, pp. 2864-2871,2005
  23. Zhigang Lu, Ying wen, Lijun Yang, "An Improved ACO algorithm in Power Distribution Systems" IEEE transactions on Power Delivery,2009
  24. H. Falaghi,M. RHaghifam, and Chanan Singh, "Ant Colony optimization-Based Method for placement of Sectionalizing Switches in Distribution Network Using a Fuzzy Multiobjective Approach' IEEE transactions on Power Delivery,Vol. 24,No. 1,pp. 268-276,2009
  25. Rajeev Annaluru,Sanjoy Das,anil Pahwa, "Multi-level Ant Colony Algorithm for Optimal Pacement of Capacitors in Distribution systems", IEEE Transactions on Power Delivery,pp. 1932-1937,2004.
  26. M. Dorigo, L. M. Gambardella, "Ant Colony System:A Cooperative Learning Approach to the Travelling salesman Problem",IEEE Transactionson Evolutionary Computations, Vol,1,pp. 53-66,1997.
  27. T. Stutzle, M. Dorigo, " A short convergence proof for a class of ant colony optimization algorithm", IEEE Transactions on Evolutionary Computation, Vol,6,Issue:4, pp. 358-365,2002.
  28. M. Dorigo and T. Stutzle, "Ant Colony Optimization",Cambridge,MA:MIT Press,2004
  29. M. Dorigo, M. Birattari, T. Stutzle " Ant colony optimization: artificial ants as a computational intelligence technique" IEEE Transactions on Evolutionary Computation, pp. 358-365,2006.
  30. Marco Dorigo, Member, IEEE, Vittorio Maniezzo, and Albert Colorni, Ant System: Optimization by a Colony of Cooperating Agents IEEE Transactions on systems, man & cybernetics-part-b cybernetics, vol 26, no. 1, February 1996,29.
  31. M. Gen, R. Cheng, Genetic algorithm and Engineering Design, John Wiley and sons Inc. ,1997
  32. Z. J. Lee, S. F. Su,C. Y. Lee, Efficiently solving general-weapon target assignment problem by genetic algorithms with greedy eugenics, IEEE Trans. System. , Man Cyber. -Part B 33 (2003) pp 113-121.
  33. J. Miller, W. Potter, R. Gandham, C. Lapena, " an evaluation of local improvement operators for genetic algorithm, IEEE transaction. System. ,man cyber 23(5), 1993,1340-1341
  34. K. Deb, A. Pratap, S. Agrawal, and T. Meyarivan, " A fast and elitist multi objective genetic algorithm:NSGA-II",IEEE Tranns. Evol. Comput. ,Vol. 6, No. 2,pp-182-197,Apr. 2002
Index Terms

Computer Science
Information Sciences

Keywords

Electric power distribution systems Priority customers Ranking based Ant colony optimization Service restoration

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