Optimal Power System Restoration and Reconfiguration in Distribution Circuit Using BFAM and BPSO
DOI: 10.4236/jemaa.2009.13025   PDF    HTML   XML   5,991 Downloads   11,454 Views   Citations


This paper approaches the problem of restoring a faulted area in an electric power distribution system after locating and isolating the faulted block and reconfiguring the system. Through this paper we are going to explain the power system restoration technique using brute-force attack method (BFAM) and binary particle swarm optimization (BPSO). This is a technique based on the possible combination in mathematical analysis which is explained in the introduction. After isolating the fault, main concentration will be towards the reconfiguration of the restored system using BPSO. Here due to fault in the system near-by agent will be affected and become useless and will go in the non-working mode. Now in order to restore these near-by loads we will give a new connection called NO (Normally Open. Using these switch system will be restored with power availability. After restoration using the BFAM, the BPSO will be used in order to provide the stable configuration. The output of the BFAM will be used as input for the BPSO and then we will reconfigure our system in order to provide the stable configuration. The effectiveness of the proposed BFAM and BPSO is demonstrated by simulating tests in a proposed distribution network and verified the results using the Matlab and C programming.

Share and Cite:

K. KUMAR and T. JAYABARATHI, "Optimal Power System Restoration and Reconfiguration in Distribution Circuit Using BFAM and BPSO," Journal of Electromagnetic Analysis and Applications, Vol. 1 No. 3, 2009, pp. 163-169. doi: 10.4236/jemaa.2009.13025.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] J. A. Momoh, and J. L. Feng, “A multi-agent-based restoration approach for NAVY ship power system,” IEEE Center for Energy Systems and Control (CESaC) Department of ECE, Howard University, Washington DC, 2009.
[2] T. Sakaguchi and K. Matsumoto, “Development of a knowledge based system for power system restoration,” IEEE Trans. Power App. Syst., Vol. PAS–102, pp. 320– 329, Feb. 1983
[3] K. Manjunath and M. R. Mohan, “A new hybrid multi-o- bjective quick service restoration technique for electric power distribution systems,” Science Direct, Electrical Power and Energy Systems, Vol. 29, pp. 51–64, 2007.
[4] M. P. Papadopoulos, G. J. Peponis, N. G. Boulaxis, and N. X. Drossoss, “Heuristic methods for the optimisation of MV distribution networks operation and planning,” Electricity Distribution Part I. Contributions. 14th International Conference and Exhibition on (IEE Conf Publ. No. 438), Vol. 6, pp. 9/1 –9/5, 2–5 June, 1997.
[5] J. Liu, P. X. Bi, Y. Q. Zhang, X. M. Wu, “Power flow analysis on simplified feeder modelling”.
[6] J. Kennedy and R. Eberhart, “Paticle swarm optimizaion,”, Proceedings, IEEE International Conference on Neural Networks, Vol. 4, pp. 1942–1948, 27 Nov.–1 Dec. 1995.
[7] J. Kennedy and R. C. Eberhart, “A discrete binary version of the particle swarm algorithm,” Systems, Man, Cybernatics, IEEE International Conference on Computational Cybernetics and Simulation, Vol. 5, pp. 4104–4108, 12– 15 Oct. 1997.
[8] A. Augugliaro, L. Dusonchet, M. G. Ippolito, and E. R. Sanseverino, “Minimum losses reconfiguration of MV distribution networks through local control of tie- switches,” IEEE Transactions on Power Delivery, Vol. 18, No. 3, pp. 762–771, July 2003.
[9] X. L. Jin, J. G. Zhao, Y. Sun, K. J. Li, and B. Q. Zhang, “Distribution network reconfiguration for load balancing using binary particle swarm optimization,” International Conference on Power System Technology-POWER- CON’04, Singapore, 21–24 Nov., 2004.
[10] T. Nagata, H. Sasaki, and R. Yokoyama, “Power system restoration by joint usage of expert system and mathematical programming approach,” IEEE Trans. Power Syst., Vol. 10, pp. 1473–1479, Aug. 1995.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.