access icon free Cuckoo search algorithm for non-convex economic dispatch

This study proposes a cuckoo search algorithm (CSA) for solving non-convex economic dispatch (ED) considering generator and system characteristics including valve-point effects, multiple fuels, prohibited zones, spinning reserve and power loss. CSA is a new meta-heuristic optimisation method inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species. When the host birds discover an alien egg in their nest, they can either throw it away or simply abandon their nest and build a new one elsewhere. The CSA idealised such breeding behaviour in combination with Lévy flights behaviour of some birds and fruit flies for applying to various constrained optimisation problems. The effectiveness of the proposed method has been tested on different non-convex ED problems. Test results have indicated that the proposed method can obtain less expensive solutions than many other methods reported in the literature. Accordingly, the proposed CSA is a promising method for solving the practical nonconvex ED problems.

Inspec keywords: concave programming; heuristic programming; power generation economics; constraint handling; search problems; power generation dispatch

Other keywords: cuckoo species; valve-point effect; spinning reserve; host bird; nonconvex economic dispatch; obligate brood parasitism; Lévy flight breeding behaviour; LeÌ�vy flight breeding behaviour; constrained optimisation problem; generator dispatch; power loss; prohibited zone; cuckoo search algorithm; CSA; alien egg; ED; multiple fuel; metaheuristic optimisation method

Subjects: Power system management, operation and economics; Optimisation techniques; Combinatorial mathematics

References

    1. 1)
      • 27. dos Santos Coelho, L., Mariani, V.C.: ‘Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect’, IEEE Trans. Power Syst., 2006, 21, (2), pp. 989996 (doi: 10.1109/TPWRS.2006.873410).
    2. 2)
      • 28. Kuo, C.-C.: ‘A novel coding scheme for practical economic dispatch by modified particle swarm approach’, IEEE Trans. Power Syst., 2008, 23, (4), pp. 18251835 (doi: 10.1109/TPWRS.2008.2002297).
    3. 3)
      • 31. Yang, X.-S., Deb, S.: ‘Cuckoo search via Lévy flights’. Proc. World Congress on Nature and Biologically Inspired Computing (NaBIC 2009), India, 2009, pp. 210214.
    4. 4)
      • 16. Gaing, Z.-L.: ‘Particle swarm optimization to solving the economic dispatch considering the generator constraints’, IEEE Trans. Power Syst., 2003, 18, (3), pp. 11871195 (doi: 10.1109/TPWRS.2003.814889).
    5. 5)
      • 33. Dieu, V.N., Schegner, P., Ongsakul, W.: ‘A newly improved particle swarm optimization for economic dispatch with valve point loading effects’. Proc. IEEE Power and Energy Society General Meeting, USA, July 2011.
    6. 6)
      • 7. Hemamalini, S., Simon, S.P.: ‘Maclaurin series-based Lagrangian method for economic dispatch with valve-point effect’, IET Gener. Transm. Distrib., 2009, 3, (9), pp. 859871 (doi: 10.1049/iet-gtd.2008.0499).
    7. 7)
      • 21. Meng, K., Wang, H.G., Dong, Z.Y., Wong, K.P.: ‘Quantum-inspired particle swarm optimization for valve-point economic load dispatch’, IEEE Trans. Power Syst., 2010, 25, (1), pp. 215222 (doi: 10.1109/TPWRS.2009.2030359).
    8. 8)
      • 5. Lin, C.E., Viviani, G.L.: ‘Hierarchical economic dispatch for piecewise quadratic cost functions’, IEEE Trans. Power Appar. Syst., 1984, PAS-103, (6), pp. 11701175 (doi: 10.1109/TPAS.1984.318445).
    9. 9)
      • 14. Liu, D., Cai, Y.: ‘Taguchi method for solving the economic dispatch problem with nonsmooth cost functions’, IEEE Trans. Power Syst., 2005, 20, (4), pp. 206214 (doi: 10.1109/TPWRS.2005.857939).
    10. 10)
      • 20. Chaturvedi, K.T., Pandit, M., Srivastava, L.: ‘Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch’, IEEE Trans. Power Syst., 2008, 23, (3), pp. 10791087 (doi: 10.1109/TPWRS.2008.926455).
    11. 11)
      • 34. Mantegna, R.N.: ‘Fast, accurate algorithm for numerical simulation of Levy stable stochastic processes’, Phys. Rev. E, 1994, 49, (5), pp. 46774683 (doi: 10.1103/PhysRevE.49.4677).
    12. 12)
      • 17. Park, J.-B., Lee, K.-S., Shin, J.-R., Lee, K.Y.: ‘A particle swarm optimization for economic dispatch with nonsmooth cost functions’, IEEE Trans. Power Syst., 2005, 20, (1), pp. 3442 (doi: 10.1109/TPWRS.2004.831275).
    13. 13)
      • 10. Chiang, C.-L., Su, C.T.: ‘Adaptive-improved genetic algorithm for the economic dispatch of units with multiple fuel options’, Cybern. Syst.: An Int. J., 2005, 36, (7), pp. 687704 (doi: 10.1080/01969720591008788).
    14. 14)
      • 23. Chen, Y.-P., Peng, W.-C., Jian, M.-C.: ‘Particle swarm optimization with recombination and dynamic linkage discovery’, IEEE Trans. Syst. Man Cybern., B, 2007, 37, (6), pp. 14601470 (doi: 10.1109/TSMCB.2007.904019).
    15. 15)
      • 32. Yang, X.-S., Deb, S.: ‘Engineering optimisation by cuckoo search’, Int. J. Math. Model. Numer. Optim., 2010, 1, (4), pp. 330343.
    16. 16)
      • 18. Park, J.-B., Jeong, Y.-W., Shin, J.-R., Lee, K.Y.: ‘An Improved particle swarm optimization for nonconvex economic dispatch problems’, IEEE Trans. Power Syst., 2010, 25, (1), pp. 156166 (doi: 10.1109/TPWRS.2009.2030293).
    17. 17)
      • 30. Mekhamer, S.F., Abdelaziz, A.Y., Kamh, M.Z., Badr, M.A.L.: ‘Dynamic economic dispatch using a hybrid Hopfield neural network quadratic programming based technique’, Electr. Power Compon. Syst., 2009, 37, (3), pp. 253264 (doi: 10.1080/15325000802454344).
    18. 18)
      • 12. Chiang, C.-L.: ‘Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels’, IEEE Trans. Power Syst., 2005, 20, (4), pp. 16901699 (doi: 10.1109/TPWRS.2005.857924).
    19. 19)
      • 8. Park, J.H., Kim, Y.S., Eom, I.K., Lee, K.Y.: ‘Economic load dispatch for piecewise quadratic cost function using Hopfield neural network’, IEEE Trans. Power Syst., 1993, 8, (3), pp. 10301038 (doi: 10.1109/59.260897).
    20. 20)
      • 24. Vlachogiannis, J.G., Lee, K.Y.: ‘Economic load dispatch – a comparative study on heuristic optimization techniques with an improved coordinated aggregation-based PSO’, IEEE Trans. Power Syst., 2009, 24, (2), pp. 9911001 (doi: 10.1109/TPWRS.2009.2016524).
    21. 21)
      • 29. Bhattacharya, A., Chattopadhyay, P.K.: ‘Hybrid differential evolution with biogeography-based optimization for solution of economic load dispatch’, IEEE Trans. Power Syst., 2010, 25, (4), pp. 19551964 (doi: 10.1109/TPWRS.2010.2043270).
    22. 22)
      • 22. Selvakumar, A.I., Thanushkodi, K.: ‘A new particle swarm optimization solution to nonconvex economic dispatch problems’, IEEE Trans. Power Syst., 2007, 22, (1), pp. 4251 (doi: 10.1109/TPWRS.2006.889132).
    23. 23)
      • 26. Niknam, T., Mojarrad, H.D., Meymand, H.Z.: ‘A new particle swarm optimization for non-convex economic dispatch’, Eur. Trans. Electr. Power, 2011, 21, (1), pp. 656679 (doi: 10.1002/etep.468).
    24. 24)
      • 19. Park, J.-B., Jeong, Y.-W., Shin, J.-R., Lee, K.Y.: ‘Closure to discussion of ‘An improved particle swarm optimization for nonconvex economic dispatch problems’, IEEE Trans. Power Syst., 2010, 25, (4), pp. 20102011 (doi: 10.1109/TPWRS.2010.2069890).
    25. 25)
      • 4. Fink, L.H., Kwatny, H.G., Mcdonald, J.P.: ‘Economic dispatch of generation via valve-point loading’, IEEE Trans. Power Appar. Syst., 1969, PAS-88, (6), pp. 805811 (doi: 10.1109/TPAS.1969.292396).
    26. 26)
      • 3. Wood, A.J., Wollenberg, B.F.: ‘Power generation, operation, and control’ (John Wiley, New York, 1996, 2nd edn.).
    27. 27)
      • 6. Lee, F.N., Breipohl, A.M.: ‘Reserve constrained economic dispatch with prohibited operating zones’, IEEE Trans. Power Syst., 1993, 8, (1), pp. 246254 (doi: 10.1109/59.221233).
    28. 28)
      • 13. Sinha, N., Chakrabarti, R., Chattopadhyay, P.K.: ‘Evolutionary programming techniques for economic load dispatch’, IEEE Trans. Evol. Comput., 2003, 7, (1), pp. 8394 (doi: 10.1109/TEVC.2002.806788).
    29. 29)
      • 1. Chowdhury, E.H., Rahrnan, S.: ‘A review of recent advances in economic dispatch’, IEEE Trans. Power Syst., 1990, 5, (4), pp. 12581259.
    30. 30)
      • 25. Vlachogiannis, J.G., Lee, K.Y.: ‘Closure to discussion on ‘Economic load dispatch – A comparative study on heuristic optimization techniques with an improved coordinated aggregation-based PSO’, IEEE Trans. Power Syst., 2010, 25, (1), pp. 591592 (doi: 10.1109/TPWRS.2009.2037534).
    31. 31)
      • 2. Xia, X., Elaiw, A.M.: ‘Optimal dynamic economic dispatch of generation: A review’, Electr. Power Syst. Res., 2010, 80, (8), pp. 975986 (doi: 10.1016/j.epsr.2009.12.012).
    32. 32)
      • 9. Walter, D.C., Sheble, G.B.: ‘Genetic algorithm solution of economic load dispatch with valve point loading’, IEEE Trans. Power Syst., 1993, 8, (3), pp. 13251332 (doi: 10.1109/59.260861).
    33. 33)
      • 15. Bhattacharya, A., Chattopadhyay, P.K.: ‘Biogeography-based optimization for different economic load dispatch problems’, IEEE Trans. Power Syst., 2010, 25, (2), pp. 10641077 (doi: 10.1109/TPWRS.2009.2034525).
    34. 34)
      • 11. Su, C.-T., Chiang, C.-L.: ‘Nonconvex power economic dispatch by improved genetic algorithm with multiplier updating method’, Electr. Power Comput. Syst., 2004, 32, (3), pp. 257273 (doi: 10.1080/15325000490208236).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2012.0142
Loading

Related content

content/journals/10.1049/iet-gtd.2012.0142
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading