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http://dx.doi.org/10.5370/JEET.2009.4.1.019

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)
Publication Information
Journal of Electrical Engineering and Technology / v.4, no.1, 2009 , pp. 19-27 More about this Journal
Abstract
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.
Keywords
Bee optimization algorithm; Economic power dispatch; Genetic algorithm; Particle swarm optimization;
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1 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
2 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   DOI   ScienceOn
3 Edwin K. P. Chong, Stanislaw H. Zak, 'An introduction to optimization', Wiley-Interscience Publication, second edition, 2004
4 I. J. Nagrath, D. P. Kothari, 'Power system engineering', Tata Mcgraw-Hill Publishing Company Limited, First edition, 1995
5 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   DOI   ScienceOn
6 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
7 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
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   DOI   ScienceOn
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   DOI   ScienceOn
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   DOI   ScienceOn
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 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
18 Happ H.H., 'Optimal power dispatch.a comprehensive survey', IEEE Trans. Power App. Syst., PAS-96, 1977, pp.841-854
19 Chowdhury B.H., Rahman S., 'A Review of recent advances in economic dispatch.' IEEE Trans. On power systems, 1990, pp. 1248-1259
20 Sung Hoon Jung. 'Queen-bee evolution for genetic algorithms', Electronics Letters, 2003, 39 (6): 575-576   DOI   ScienceOn
21 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   DOI
22 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   DOI   ScienceOn
23 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   DOI   ScienceOn