Distribution Systems Reconfiguration using a modified particle swarm optimization algorithm

Electric Power Systems Research

Volumn 79, Issue 11, 2009, Pages 1521-1530

  Abdelaziz, A Y ^a   Mohammed, F M ^a   Mekhamer, S F ^a   Badr, M A L ^a  

^a The British University in Egypt   (Egypt)

Author keywords

Distribution Systems Reconfiguration; Loss reduction; Particle swarm optimization

Indexed keywords

BIRD FLOCKS; COMPARATIVE STUDIES; DISTRIBUTION SYSTEMS; DISTRIBUTION SYSTEMS RECONFIGURATION; EVOLUTION ALGORITHMS; FISH SCHOOL; INERTIA WEIGHT; LOSS REDUCTION; MODIFIED PARTICLE SWARM OPTIMIZATION; NUMBER OF ITERATIONS; OPTIMAL DISTRIBUTIONS; OPTIMIZATION PROBLEMS; PARTICLE SWARM OPTIMIZATION ALGORITHM; POPULATION SIZES; POWER-LOSSES; PSO ALGORITHMS; SOCIAL BEHAVIOR;

ALGORITHMS; LOCAL AREA NETWORKS; POPULATION STATISTICS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 68549105907     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.epsr.2009.05.004     Document Type: Article

References (29)

1. Civanlar S., Grainger J.J., and Lee S.H. Distribution feeder reconfiguration for loss reduction. IEEE Transactions on Power Delivery 3 July (3) (1988) 1217-1223
2. Baran M.E., and Wu F.F. Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Transactions on Power Delivery 4 April (2) (1989) 1401-1407
3. Taylor T., and Lubkeman D. Implementation of heuristic search strategies for distribution feeder reconfiguration. IEEE Transactions on Power Delivery 5 January (1) (1990) 239-246
4. Wagner T.P., Chikhani A.Y., and Hackam R. Feeder reconfiguration for loss reduction: an application of distribution automation. IEEE Transactions on Power Delivery 6 October (4) (1991) 1922-1931
5. Sarfi R.J., Salama M.M.A., and Chikhani A.Y. Distribution system reconfiguration for loss reduction: an algorithm based on partitioning theory. IEEE Transactions on Power Systems 11 February (1) (1996) 504-510
6. Chiang H.D., and Jean-Jumeau R. Optimal network reconfigurations in distribution systems: part II. IEEE Transactions on Power Delivery 5 July (3) (1990) 1568-1574
7. Chang H.-C., and Kuo C.-C. Network reconfiguration in distribution systems using simulated annealing. Electric Power Systems Research 29 May (3) (1994) 227-238
8. Nara K., Shiose A., Kitagawa M., and Ishihara T. Implementation of genetic algorithm for distribution systems loss minimum reconfiguration. IEEE Transactions on Power Systems 7 August (3) (1992) 1044-1051
9. Kim H., Ko Y., and Jung K. Artificial neural network based feeder reconfiguration for loss reduction in distribution systems. IEEE Transactions on Power Delivery 8 July (3) (1993) 1356-1366
10. H. Mori, Y. Ogita, A parallel tabu search method for reconfiguration of distribution systems, Proceedings of the 2000 IEEE Power Engineering Society Summer Meeting, vol. 1, pp. 73-78.
11. Li K.K., Chung T.S., Chen G.J., and Tang G.Q. A tabu search approach to distribution network reconfiguration for loss reduction. Electric Power Components and Systems 32 June (6) (2004) 571-585
12. Jeon Y.-J., and Kim J.-C. Application of simulated annealing and tabu search for loss minimization in distribution systems. Electric Power and Energy Systems 26 January (1) (2004) 9-18
13. Mekhamer S.F., Abdelaziz A.Y., Mohammed F.M., and Badr M.A.L. A new intelligent optimization technique for Distribution Systems Reconfiguration. Proceedings of the Twelfth International Middle-East Power Systems Conference MEPCON'2008, South Valley University. Aswan, Egypt, March (2008) 397-401
14. Su C.-T., Chang C.-F., and Chiou J.-P. Distribution network reconfiguration for loss reduction by ant colony search algorithm. Electric Power Systems Research 75 August (2-3) (2005) 190-199
15. Naka S., Genji T., Yura T., and Fukuyama Y. A hybrid particle swarm optimization for distribution state estimation. IEEE Transactions on Power Systems 18 February (1) (2003) 60-68
16. Kannan S., Slochanal S.M.R., Subbaraj P., and Padhy N.P. Application of particle swarm optimization technique and its variants to generation expansion planning problem. Electric Power Systems Research 70 August (3) (2004) 203-210
17. Yu X.M., Xiong X.Y., and Wu Y.W. A PSO-based approach to optimal capacitor placement with harmonic distortion consideration. Electric Power Systems Research 71 September (1) (2004) 27-33
18. Chao-Ming H., Chi-Jen H., and Ming-Li W. A particle swarm optimization to identifying the ARMAX model for short-term load forecasting. IEEE Transactions on Power Systems 20 May (2) (2005) 1126-1133
19. Alrashidi M.R., and El-Hawary M. A survey of particle swarm optimization applications in power system operations. Electric Power Components and Systems 34 December (12) (2006) 1349-1357
20. Saravanan M., Slochanal S.M.R., Venkatesh P., and Abraham J.P.S. Application of particle swarm optimization technique for optimal location of FACTS devices considering cost of installation and system loadability. Electric Power Systems Research 77 March (3-4) (2007) 276-283
21. Arya L.D., Choube S.C., Shrivastava M., and Kothari D.P. Particle swarm optimization for determining shortest distance to voltage collapse. Electrical Power and Energy Systems 29 December (10) (2007) 796-802
22. Yumbla P.E.O., Ramirez J.M., and Coello C.A. Optimal power flow subject to security constraints solved with a particle swarm optimizer. IEEE Transactions on Power Systems 23 February (1) (2008) 33-40
23. del Valle Y., Venayagamoorthy G.K., Mohagheghi S., Hernandez J.C., and Harley R.G. Particle swarm optimization: basic concepts, variants and applications in power systems. IEEE Transactions on Evolutionary Computation 12 April (2) (2008) 171-195
24. Sivanagaraju S., Rao J.V., and Raju P.S. Discrete particle swarm optimization to network reconfiguration for loss reduction and load balancing. Electric Power Components and Systems 36 May (5) (2008) 513-524
25. J. Kennedy, R. Eberhart, Particle swarm optimization, Proceedings of the 1995 IEEE Neural Networks Conference, Piscataway, NJ, pp. 1942-1948.
26. Y. Shi, R. Eberhart, A modified particle swarm optimizer, Proceedings of the IEEE Computation Intelligence World Congress, May 1998, pp. 69-73.
27. F. Van den Bergh, An analysis of particle swarm optimizer, Ph. D. Dissertation, Faculty of Natural and Agricultural Science, University of Pretoria, South Africa, 2001.
28. Shi Y., and Eberhart R.C. Empirical study of particle swarm optimization. Proceedings of the IEEE Evolutionary Computation Congress, vol. 3, July (1999) 1945-1950
29. Eberhart R., and Shi Y. Particle swarm optimization: developments, applications and resources. Proceedings of the IEEE Evolutionary Computation Congress, vol. 1, May (2001) 81-86