An evolutionary approach for optimal time interval determination in distribution network reconfiguration under variable load

Mathematical and Computer Modelling

Volumn 57, Issue 1-2, 2013, Pages 68-77

  Milani, Armin Ebrahimi ^a   Haghifam, Mahmood Reza ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b TARBIAT MODARES UNIVERSITY   (Iran)

Author keywords

Distribution network; Genetic algorithm; Optimal time interval; Reconfiguration; Time varying load

Indexed keywords

BINARY PARTICLE SWARM OPTIMIZATION; BUS NETWORKS; DISTRIBUTION NETWORK RECONFIGURATION; EVOLUTIONARY APPROACH; NUMERICAL RESULTS; OPTIMAL DYNAMICS; OPTIMAL RECONFIGURATIONS; OPTIMAL TIME; OPTIMIZATION PROCEDURES; POWER LOSS REDUCTION; POWER-LOSSES; RECONFIGURATION; RECONFIGURATION MODEL; TIME POINTS; TIME VARYING LOADS; TOTAL BENEFITS; VARIABLE LOADS;

DYNAMIC MODELS; ELECTRIC POWER DISTRIBUTION; GENETIC ALGORITHMS; NUMERICAL METHODS;

OPTIMIZATION;

EID: 84866167094     PISSN: 08957177     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mcm.2011.05.047     Document Type: Article

References (27)

1. Civanlar S., Grainger J.J., Yin H., Lee S.S.H. Distribution feeder reconfiguration for loss reduction. IEEE Trans. Power Deliv. 1988, 3:1217-1223.
2. Baran M., Wu F. Network reconfiguration in distribution system for loss reduction and load balancing. IEEE Trans. Power Deliv. 1989, 2:1401-1407.
3. Shirmohammadi D., Hong H.W. Reconfiguration of electric distribution networks for resistive line losses reduction. IEEE Trans. Power Deliv. 1989, 4:1492-1498.
4. Shirmohammadi D., Hong H.W., Semlyen A., Luo G.X.A. A compensation based power flow method for weakly meshed distribution and transmission networks. IEEE Trans. Power Syst. 1988, 3:753-762.
5. Nara K., Shiose A., Kitagawa M., Ishihara T. Implementation of a genetic algorithm for distribution systems loss minimum re-configuration. IEEE Trans. Power Syst. 1992, 7:1044-1051.
6. Sarfi R., Salama M., Chikhani Y. Distribution system reconfiguration for loss reduction: an algorithm based on network partitioning theory. IEEE Trans. Power Syst. 1996, 11:504-510.
7. Delbem A.C.B., Bretas N.G., De Carvalho A. Distribution system reconfiguration using graph chain representation. Proc. Int. Conf. Power Syst. Technol. 2000, 1:439-443.
8. Jin X., Zhao J., Sun Y., Li K., Zhang B. Distribution network reconfiguration for load balancing using binary particle swarm optimization. Proc. Int. Conf. Power Syst. Technol. 2004, 1:500-510.
9. Salazar H., Gallego R., Romero R. Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems. IEEE Trans. Power Deliv. 2006, 3:1735-1742.
10. Das D. A fuzzy multi-objective approach for network reconfiguration of distribution systems. IEEE Trans. Power Deliv. 2006, 21:1401-1407.
11. Tu Q., Guo Z.Z. Median current moment method for dynamic reconfiguration in distribution network. Proc. Int. Conf. Power Syst. Technol. 2006, 1-4.
12. H. Yang, Y. Peng, N. Xiong, Gradual approaching method for distribution network dynamic reconfiguration, in: Proc. 2008 Workshop on Power Electronics and Intelligent Transportation Syst., 2008, pp. 257-260.
13. Yin S., Lu C. Distribution feeder scheduling considering variable load profile and outage costs. IEEE Trans. Power Syst. 2009, 24:652-660.
14. Youman D., Boming Z., Tian T. A fictitious load algorithm and its application to distribution network dynamic optimizations. Proc. CSEE 1996, 16:241-244.
15. Li-yan YIN, Ji-lai YU Dynamic reconfiguration of distribution network with multi-time periods. Proc. CSEE 2002, 22:44-48.
16. Jian-zhong WU, Yi-xin YU Global optimization algorithm to time varying reconfiguration for operation cost minimization. Proc. CSEE 2003, 23:13-17.
17. Sivanandam S.N., Deepa S.N. Introduction to Genetic Algorithms 2010, Springer Pub., New York. 1st ed.
18. Holland J.H. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence 1975, The University of Michigan Press, USA. 2nd ed.
19. Ho-Chung Leung, Genetic algorithm for optimal capacitor selection and optimal power flow with facts devices, Thesis (Ph.D.), Hong Kong Polytechnic University, 2004.
20. G. Sywerda, Uniform crossover in genetic algorithms, in: Proceedings of the 3rd International Conference on Genetic Algorithms, USA, 1989.
21. J. Page, P. Poli, W.B. Langdon, Smooth uniform crossover with smooth point mutation in genetic programming: a preliminary study, in: Genetic Programming, Proceedings of EuroGP'99, Sweden, 1999.
22. E. Falkenauer, The worth of uniform crossover, in: Proceedings of the 1999 Congress on Evolutionary Computation, vol. 1, 1999, p. 782.
23. R.T.F. Ah King, B. Radha, H.C.S. Rughooputh, A real-parameter genetic algorithm for optimal network reconfiguration, in: IEEE International Conf. on Industrial Tech., vol. 1, 2003, pp. 54-59.
24. Kaelo P., Ali M.M. Integrated crossover rules in real coded genetic algorithms. European J. Oper. Res. 2007, 176:60-76.
25. Tsoulos I.G. Modifications of real code genetic algorithm for global optimization. Appl. Math. Comput. 2008, 203:598-607.
26. J. Zhu, X. Xiong, D. Hwang, A. Sadjadpour, A comprehensive method for reconfiguration of electrical distribution network, in: IEEE Power Eng. Soc. General Meeting, 2007, pp. 1-7.
27. Yin Shih-An, Lu Chan-Nan Distribution feeder scheduling considering variable load profile and outage costs. IEEE Trans. Power Syst. 2009, 24:652-660.