Using Constraint Programming for Reconfiguration of Electrical Power Distribution Networks

  • Juan Francisco Díaz
  • Gustavo Gutierrez
  • Carlos Alberto Olarte
  • Camilo Rueda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3389)


The problem of reconfiguring power distribution systems to reduce power losses has been extensively studied because of its significant economic impact. A variety of approximation computational models have recently been proposed. We describe a constraint programming model for this problem, using the Mozart system. To handle real world reconfiguration systems we implemented and integrated into Mozart an efficient constraint propagation system for the real numbers. We show how the CP approach leads to a simpler model and allows more flexible control of reconfiguration parameters. We analyze the performance of our system in canonical distribution networks of up to 60 nodes. We describe how the adaptability of the Mozart search engine allows defining effective strategies for tackling a real distribution system reconfiguration of around 600 nodes.


Constraint Programming Constraint System Interval Arithmetic Operational Constraint Real Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Baran, M.E., Wu., F.F.: Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Transactions on Power Delivery 4(2), 1401–1407 (1989)CrossRefGoogle Scholar
  2. 2.
    Benhamou, F., Goualard, F., Granvilliers, L.: Revising hull and box consistency. In: Proceedings of ICLP 1999, pp. 230–244. MIT Press, Cambridge (1999)Google Scholar
  3. 3.
    Caicedo, G.: Nueva propuesta en reconfiguracion de alimentadores utilizando programacion con restricciones, PhD thesis, Universidad del Valle, Cali, Colombia (2004)Google Scholar
  4. 4.
    Civanlar, S., Grainger, J.J., Yin, H., Lee, S.S.: Distribution feeder reconfiguration for loss reduction. IEEE Transactions on Power Delivery 3(3), 1217–1223 (1988)CrossRefGoogle Scholar
  5. 5.
    Creemers, T., Ros, L., Riera, J., Ferrarons, C., Roca, J., Corbella, X.: Constraint-based maintenance scheduling on an electric power-distribution network. In: Third International Conference and Exhibition on Practical Applications of Prolog (April 1995)Google Scholar
  6. 6.
    Creemers, T., Ros, L., Riera, J., Ferrarons, C., Roca, J., Corbella, X.: Programación optima de tareas de mantenimiento y reconfiguración sobre redes de media tensión. In: The Fourth Portuguese-Spanish Conference on Electrical Engineering (July 1995)Google Scholar
  7. 7.
    Fukuyama, Y.: Reactive tabu search for distribution load transfer operation. In: IEEE PES winter meeting, Singapore (January 2000)Google Scholar
  8. 8.
    Fukuyama, Y., Chiang, H.D.: Modern heuristic techniques for combinatorial problem. In: Proc. of IEEE FUZZ/IFES conference, Yokohama (March 1995)Google Scholar
  9. 9.
    Hickey, T., Ju, Q., Van Emden, M.H.: Interval arithmetic: From principles to implementation. Journal of the ACM 48(5), 1038–1068 (2001)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Jeon, Y.J., Kim, J.C., Kim, J.O., Shin, J.R., Lee, K.Y.: An efficient simmulated annealing algorithm for network reconfiguration in large-scale distribution systems. IEEE Transactions on Power Delivery 17(4), 1070–1078 (2002)CrossRefGoogle Scholar
  11. 11.
    Lhomme, O.: Consistency techniques for numeric csps. In: Proceedings of the 13th IJCAI, pp. 232–238. IEEE Computer Society Press, Los Alamitos (1993)Google Scholar
  12. 12.
    Müller, T.: Adding constraint systems to DFKI Oz. In: WOz 1995, International Workshop on Oz Programming, Institut Dalle Molle d’Intelligence Artificielle Perceptive, Martigny, Switzerland, November 29– December 1(1995)Google Scholar
  13. 13.
    Neumaier, A.: Interval methods for system of equations. Cambridge University Press, Cambridge (1990)Google Scholar
  14. 14.
    Shirmohammadi, H., Hong, W.: Reconfiguration of electric distribution networks for resistive line losses reduction. IEEE Transactions on Power Delivery 4(2), 1492–1498 (1989)CrossRefGoogle Scholar
  15. 15.
    Smolka, G.: A foundation for higher-order concurrent constraint programming. In: Jouannaud, J.-P. (ed.) CCL 1994. LNCS, vol. 845, pp. 50–72. Springer, Heidelberg (1994)CrossRefGoogle Scholar
  16. 16.
    Su, C.T., Lee, C.S.: Feeder reconfiguration and capacitor setting for loss reduction of distribution systems. Elect. Power Syst. Res. 58(2), 97–102 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Juan Francisco Díaz
    • 2
  • Gustavo Gutierrez
    • 1
  • Carlos Alberto Olarte
    • 1
  • Camilo Rueda
    • 1
  1. 1.Pontificia Universidad JaverianaCaliColombia
  2. 2.Universidad del ValleCaliColombia

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