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Application of evolutionary algorithms and classifier systems for optimisation of the operation of electric power distribution networks

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The problem of optimising the configuration of electric power distribution networks during changing loadings and in malfunction conditions of the network is a task of multi-criteria optimisation. In the article is presented the co-evolutionary algorithm with memory at the population level, enabling the search for pareto-optimal solutions such as are in the analysed task of network configurations. The drawn up method is used in the organisation of evolutionary algorithm memory uses the theoretical bases of classifying systems. The method presented in the article enables effective search of optimal configurations of distribution networks for various network loadings and also network malfunction conditions.
Czasopismo
Rocznik
Tom
Strony
3894--3907
Opis fizyczny
Bibliogr. 18 poz., rys., tab., pełen tekst na CD
Twórcy
autor
  • Politechnika Świętokrzyska w Kielcach
Bibliografia
  • 1.Liu C. C., Lee S. J., Venkata S. S.: An expert system operational aid for restoration and loss reduction of distribu¬tion system. IEEE Trans. on Power Delivery, vol. 3, 1988, pp. 619-629.
  • 2.Hsu Y. Y., Huang M.: Distribution system service restoration using a heuristic search approach. IEEE Trans. on Power Delivery, vol. 7, 1992, pp. 734-740.
  • 3.Fukuyama Y., Chiang H. D.: Parallel genetic algorithm for service restoration in electric power distribution sys¬tems. Electric Power & Energy Systems. vol. 18, no. 2, 1996, pp. 111-119.
  • 4.Miu K. N., Chiang H. D., Yuan B.: Fast service restoration for large-scale distribution systems with priority cus¬tomers and constraints. IEEE Trans. on Power Systems, vol. 13. no. 3, Aug. 1998, pp. 789-795.
  • 5.Morelato A. L., Monticelli A. J.: Heuristic search approach to distribution system restoration. IEEE Trans. Power Delivery, vol. 4, Oct. 1989, pp. 2235-2241.
  • 6.Tomsovic S. Wu. K. L., Chen C. S.: A heuristic search approach to feeder switching operations for overload, faults, unbalanced flow and maintenance. IEEE Trans. Power Delivery. vol. 6. Oct. 1991, pp. 1579-1586.
  • 7.Hsiao Y., Chien C.: Enhancement of restoration service in distribution systems using a combination fuzzy-GA method. IEEE Trans. Power Systems, vol. 15, Nov. 2000, pp. 1394-1400.
  • 8.Toune S., Fudo H., Genji T., Fukuyama Y.: Comparative study of modern heuristic algorithms to service restora¬tion in distribution systems. IEEE Trans. Power Delivery, vol. 17, Jan. 2002, pp. 173-181.
  • 9.Chao-Shun C., Lin C-H., Hung-Ying T.: A rule-based expert system with colored petri net models for distribution system service restoration. IEEE Trans. Power Systems, vol. 17, Nov. 2002, pp. 1073-1080.
  • 10.Khushalani S., Solanki, J.M., Schulz, N.N. Optimized Restoration of Unbalanced Distribution Systems. IEEE Transactions on Power Systems, no. 22, Issue 2. 2007, p. 624-630.
  • 11.Kumar Y., Das, B., Sharma, J. Multiobjective, Multiconstraint Service Restoration of Electric Power Distribution System With Priority Customers. IEEE Transactions on Power Delivery, no. 23, Issue 1, 2008, p. 261-270.
  • 12.Delbem A. C. B., Carvalho A. C. P. L. F., Bretas N. G.: Main chain representation for evolutionary algorithms ap¬plied to distribution system reconfiguration. IEEE Trans. Power Systems., vol. 20, no. 1, Feb. 2005, pp. 425-436.
  • 13.Nara K., Shiose A., Kitagawa M., Ishihara T.: Implementation of genetic algorithm for distribution systems loss minimum reconfiguration. IEEE Trans. Power Systems, vol. 7, no. 3, Aug. 1992, pp. 1044-1051.
  • 14.Shayeghi H., Mahdavi M.: Genetic algorithm based studying of bundle lines effect on network losses in transmis¬sion network expansion planning. Journal of Electrical Engineering-Elektrotechnicky Casopis, Vol 60, 5 (2009) p. 237-245.
  • 15.Hong Y. Y., Ho S. Y.: Determination of network configuration considering multiobjective in distribution systems using genetic algorithms. IEEE Trans. Power Systems, vol. 20, no. 2, May 2005, pp. 1062-1069.
  • 16.Goldberg D. E. Genetic Algorithms and Their Applications. WNT, Warszawa 2003.
  • 17.Filipiak S.: Application of Evolutionary Algorithm in Optimisation of Medium-Voltage Distribution Networks Post-Fault Configuration., International Journal of Electrical Power & Energy Systems Volume 44, Issue 1, Janu¬ary 2013, Pages 666–671.
  • 18.Stępień J.: Evaluation of structural redundancy effects in medium voltage cable networks. Przegląd Elektrotech¬niczny Volume: 84 Issue: 4 p. 128-131 Published: 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c28ff9b8-b551-427b-aa83-4e9accfb8ed2
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