A Modified Shuffled Frog Leaping Algorithm for Long-Term Generation Maintenance Scheduling

  • G. Giftson Samuel
  • C. Christober Asir Rajan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 258)


This paper discuss a modified Shuffled frog leaping algorithm to Long-term Generation Maintenance Scheduling to Enhance the Reliability of the units. Maintenance scheduling establishes the outage time scheduling of units in a particular time horizon. In a monopolistic power system, maintenance scheduling is being done upon the technical requirements of power plants and preserving the grid reliability. While in power system, technical viewpoints and system reliability are taken into consideration in maintenance scheduling with respect to the economical viewpoint. In this paper present a modified Shuffled frog leaping algorithm methodology for finding the optimum preventive maintenance scheduling of generating units in power system. The objective function is to maintain the units as earlier as possible. Varies constrains such as spinning reserve, duration of maintenance and maintenance crew are being taken into account. In case study, test system consist of 24 buses with 32 thermal generating units is used.


Generation maintenance schedule Optimization Shuffled frog leaping algorithm 


  1. 1.
    Cohen, A., Sherkat, V.: Optimization based methods for operations scheduling. Proc. IEEE 75(12), 1574–1591 (1987)CrossRefGoogle Scholar
  2. 2.
    Renaud, A.: Daily generation management at electricity de france: from planning towards real time. IEEE Trans. Autom. Control 38(7), 1080–1093 (1993)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Ferreira, L.A., Anderson, T., Imparato, C.F., Vojdani, A.F.: Short term resource scheduling in multi-area hydrothermal power systems. Electr. Power Energy Syst. 11(3), 200–212 (1989)Google Scholar
  4. 4.
    Shaw J.J., Bertsekas, D.P.: Optimal scheduling of large hydrothermal power system. IEEE Trans. Power Apparatus Syst. (PAS) 104, 286–293 (1985)Google Scholar
  5. 5.
    Shaw, J.: A direct method for security constrain unit commitment, pp. 25–31. IEEE/PES Summer Meeting, San Francisco (1994)Google Scholar
  6. 6.
    El-Kaib, A., Ma, H., Hart, J.: Environmentally constrained economic dispatch using Lagrangian relaxation method. IEEE Trans. Power Syst. 9(4), 1723–1729 (1994)CrossRefGoogle Scholar
  7. 7.
    Guan, X., Luh, P.B.: Power system scheduling with fuzzy reserve requirements. IEEE Trans. Power Syst. 11(2), 864–869 (1996)CrossRefGoogle Scholar
  8. 8.
    Tomsovic, Y.: A fuzzy linear programming approach to the reactive power/voltage control problem. IEEE Trans. Power Syst. 7(1), 287–293 (1992)CrossRefGoogle Scholar
  9. 9.
    Miranda, V., Saraiva, J.T.: Fuzzy modeling of power system optimal load flow. IEEE Trans. Power Syst. 7(2), 843–849 (1992)CrossRefGoogle Scholar
  10. 10.
    Li, Y., Luh, P.B., Guan, X.: Fuzzy optimization-based scheduling of identical machines with possible breakdown. In: Proceedings of IEEE 1994 International Conference on Robotics, San Diego, pp. 3347–3452 (1994)Google Scholar
  11. 11.
    Shahidehpour, M., Marwali, M.: Maintenance scheduling in restructured power system. Kluwer, Norwell (2000)Google Scholar
  12. 12.
    Leou, R.C.: A Flexible unit maintenance scheduling considering uncertainties. IEEE Trans. Power Syst. 16(3), 552–559 (2001)Google Scholar
  13. 13.
    Endrenyi, J.: The present status of maintenance strategies and the impact of maintenance on reliability. IEEE Trans. Power Syst. 16(4), 638–646 (2001)Google Scholar
  14. 14.
    Yamin, H.Y., Shahidehpour, S.M.: Long-term transmission and generation maintenance scheduling with network, fuel and emission constraints. IEEE Trans. Power Syst. 14(3), 1160–1165 (1999) Google Scholar
  15. 15.
    Rajan, C.C.A., Mohan, M.R., An evolutionary programming based tabu search for solving the unit commitment problem. IEEE Trans. Power Syst. 19(1), 577–589 (2004)Google Scholar
  16. 16.
    Eusuff, M.M., Lansey, K.E., Pasha, F.: Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Eng. Optim. 38(2), 129–154 (2006)CrossRefMathSciNetGoogle Scholar
  17. 17.
    Zhang, X., Hu, X., Cui, G., Wang, Y., Niu, Y.: An improved shuffled frog leaping algorithm with cognitive behavior. In: Proceedings of the 7th World Congress Intelligent Control and Automation (2008)Google Scholar
  18. 18.
    Eslamian, M., Hosseinian, S.H., Vahidi, B.: Bacterial foraging-based solution to the unit-commitment problem. IEEE Trans. Power Syst. 24(3), 1478–1488 (2009)CrossRefGoogle Scholar
  19. 19.
    Elbehairy, H., Elbeltagi, E., Hegazy, T.: Comparison of two evolutionary algorithms for optimization of bridge deck repairs. Comput. Aided Civ. Infrastruct. Eng. 21, 561–572 (2006)CrossRefGoogle Scholar
  20. 20.
    Rahimi-Vahed, A., Mirzaei, A.H.: Solving a bi-criteria permutation flow-shop problem using shuffled frog-leaping algorithm. In: Soft Computing. Springer-Verlag, New York (2007)Google Scholar
  21. 21.
    Luo, X.-H., Yang, Y., Li, X.: Solving TSP with shuffled frog-leaping algorithm. Proc. ISDA 3, 228–232 (2008)Google Scholar
  22. 22.
    Elbeltagi, E., Hegazy, T., Grierson, D.: Comparison among five evolutionary-based optimization algorithms. Adv. Eng. Inf. 19(1), 43–53 (2005)Google Scholar
  23. 23.
    Kennedy, J., Eberhart, R.C.: Particle swarm optimization. Proc. IEEE Conf. Neural Netw. 4, 1942–1948 (1995)Google Scholar
  24. 24.
    Huynh, T.H.: A modified shuffled frog leaping algorithm for optimal tuning of multivariable PID controllers. In: Proceedings of the ICIT 2008, pp. 1–6Google Scholar
  25. 25.
    The IEEE reliability test system—1996. IEEE Trans. Power Syst. 14(3), 1010–1020 (1999) Google Scholar
  26. 26.
    Elbeltagi, E., Hegazy, T., Grierson, D.: A modified shuffled frog leaping optimization algorithm: application to project management. Struct. Infrastruct. Eng. 3(1), 53–60 (2007)CrossRefGoogle Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  • G. Giftson Samuel
    • 1
  • C. Christober Asir Rajan
    • 2
  1. 1.Department of EEEAnna UniversityChennaiIndia
  2. 2.Department of EEEPondicherry Engineering CollegePondicherryIndia

Personalised recommendations