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Economic Power Dispatch with Valve Point Effects Using Bee Optimization Algorithm

  • Kumar, Rajesh (Dept. of Electrical Engineering, Malaviya National Institute of Technology) ;
  • Sharma, Devendra (Dept. of Electrical Engineering, Malaviya National Institute of Technology) ;
  • Kumar, Anupam (Dept. of Electronics and Communication Engineering, Malaviya National Institute of Technology)
  • 발행 : 2009.03.01

초록

This paper presents a newly developed optimization algorithm, the Bee Optimization Algorithm (BeeOA), to solve the economic power dispatch (EPD) problem. The authors have developed a derivative free and global optimization technique based on the working of the honey bee. The economic power dispatch problem is a nonlinear constrained optimization problem. Classical optimization techniques fail to provide a global solution and evolutionary algorithms provide only a good enough solution. The proposed approach has been examined and tested on two test systems with different objectives. A simple power dispatch problem is tested first on 6 generators and then the algorithm is demonstrated on 13 thermal unit systems whose incremental fuel cost function takes into account the value point loading effect. The results are promising and show the effectiveness and robustness of the proposed approach over recently reported methods.

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참고문헌

  1. Qin, L.D., Jiang, Q.Y., Zou, Z.Y., Cao, Y.J., 'A queenbee evolution based on genetic algorithm for economic power dispatch', IEEE Universities Power Engineering Conference, 2004. Vol 1, 2004, pp. 453-456, Vol. 1
  2. Happ H.H., 'Optimal power dispatch.a comprehensive survey', IEEE Trans. Power App. Syst., PAS-96, 1977, pp.841-854
  3. Chowdhury B.H., Rahman S., 'A Review of recent advances in economic dispatch.' IEEE Trans. On power systems, 1990, pp. 1248-1259
  4. Sung Hoon Jung. 'Queen-bee evolution for genetic algorithms', Electronics Letters, 2003, 39 (6): 575-576 https://doi.org/10.1049/el:20030383
  5. Thomas D. Seeley, P.Kirk Visscher & Kevin M.Passino, 'Group decision making in honey bee swarms', American scientist, vol.94, Issue 3, 2006, pp. 220-229 https://doi.org/10.1511/2006.59.993
  6. Kevin M.Passino, Thomas D. Seeley & P.Kirk Visscher, 'Swarm Coginition In Honey Bee', Behavioral Ecology and Sociobiology, vol. 62, no. 3, pp.401-414, 2008 https://doi.org/10.1007/s00265-007-0468-1
  7. K. M. Passino and T. D. Seeley, 'Modeling and analysis of nest site selection by honey bee swarms: The speed and accuracy trade-off', Behavioral Ecology and Sociobiology, vol 59, no.3, pp.427-442, 2006 https://doi.org/10.1007/s00265-005-0067-y
  8. T. Seeley, S. Camazine, and J. Sneyd, 'Collective decision-making in honey bees: how colonies choose among nectar sources', Behavioral Ecology and Sociobiology, vol. 28, 19991, pp. 277-290
  9. Chin soon Cong, Malcolm Yoke hean Low, Appa Iyer Sivakurnar, Kheng Leng Gay, 'A bee Colony Optimization algorithm To Job Scheduling', Simulation Conference, 2006. WSC 06. Proceedings of the Winter, pp. 1954-1961
  10. J. Liu yanfei, Passino K.M., 'Biomimìciry of social foraging behavior for distributed optimization models, principles & emergent behaviours', Jounral of Optimization theory and Applications, vol.115, 2002, pp. 603-628 https://doi.org/10.1023/A:1021207331209
  11. Kalyan Moy DEB 'Multi-Objective Optimization using Evolutionary Algotirhms', John Wiley & Sons, Ltd, 2002
  12. Edwin K.P. Chong, Stanislaw H. Zak, 'An Introduction to Optimization', Second Edition, Wiley-Interscience Publication
  13. M. Dorigo, L. Gambardella, M. Middendorf, and T. Stutzle, 'Guest editorial: special section on ant colony optimization', IEEE Transactions on Evolutionary Computation, vol. 6, 2002, pp. 317-319 https://doi.org/10.1109/TEVC.2002.802446
  14. M. Dorigo, V Maniezzo, and A. Colomi, 'Ant system: optimization by a colony of cooperating agents', IEEE Trans. on Systems, Man and Cybemetics, Part B, vol. 26, 1996, pp.29-41 https://doi.org/10.1109/3477.484436
  15. David E. Goldberg, 'Genetic Algorithms in Search, Optimization, and Machine Leaming', Pearson Education, ninth Edition, 2005
  16. D.T Pham, Anthony J.Sokaka , Afshin Ghanbarzadeh, Ebubekir Koc, Sameh Otri, Michael Packianather, 'Optimising Neural Networks for Identification of Wood Defects Using the Bees Algorithm', IEEE lnternational Conference on lndzιstrial lnformatics, 2006, pp. 1346-1351
  17. Dusan Teodorovic, Patna Lucic, Goran Markovic, Mauro Dell Orco, 'Bee colony Optimization: Principles and applications', Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar, 2006, pp. 151-156
  18. M. Cox and M. Myerscough, 'A flexible model offoraging by a honey bee colony: the effects of individual behavior on foraging success', Journal of Theoretical Biology, vol. 223, 2003, pp. 179-197 https://doi.org/10.1016/S0022-5193(03)00085-7
  19. Edwin K. P. Chong, Stanislaw H. Zak, 'An introduction to optimization', Wiley-Interscience Publication, second edition, 2004
  20. I. J. Nagrath, D. P. Kothari, 'Power system engineering', Tata Mcgraw-Hill Publishing Company Limited, First edition, 1995
  21. T. A. A. Victoirε and A.E Jevakurnar, 'Hybrid PSOSQP for economic dispatch with valve-point effect', Electric power Systems Research, vol. 71, no. 1, pp. 51- 59, 2004 https://doi.org/10.1016/j.epsr.2003.12.017
  22. N. Sinha, R. Chakrabarti, and P. K. Chattopadhyay, 'Evolutionary programming techniques for economic load dispatch', IEEE Transactions on Evolutionary Computation, vol. 7, no. 1, pp. 83-94
  23. L. S. Coellio and V C. Mariani, 'Economic Dispatch Optimization Using Hybrid Chaotic Particle Swarm Optimizer', IEEE lnternational Conference on Systems, Man and Cybernetics, 2007, pp. 1963-1968

피인용 문헌

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