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http://dx.doi.org/10.5370/JEET.2008.3.3.320

An Improved Dynamic Programming Approach to Economic Power Dispatch with Generator Constraints and Transmission Losses  

Balamurugan, R. (Department of Electrical Engineering, Annamalai University)
Subramanian, S. (Department of Electrical Engineering, Annamalai University)
Publication Information
Journal of Electrical Engineering and Technology / v.3, no.3, 2008 , pp. 320-330 More about this Journal
Abstract
This paper presents an improved dynamic programming (IDP) approach to solve the economic power dispatch problem including transmission losses in power systems. A detailed mathematical derivation of recursive dynamic programming approach for the economic power dispatch problem with transmission losses is presented. The transmission losses are augmented with the objective function using price factor. The generalized expression for optimal scheduling of thermal generating units derived in this article can be implemented for the solution of the economic power dispatch problem of a large-scale system. Six-unit, fifteen-unit, and forty-unit sample systems with non-linear characteristics of the generator, such as ramp-rate limits and prohibited operating zones are considered to illustrate the effectiveness of the proposed method. The proposed method results have been compared with the results of genetic algorithm and particle swarm optimization methods reported in the literature. Test results show that the proposed IDP approach can obtain a higher quality solution with better performance.
Keywords
Dynamic programming; Economic power dispatch; Optimization; Prohibited operating zones; Ramp-rate constraints;
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  • Reference
1 D.E. Goldberg, "Genetic algorithm in search, optimization and machine learning", Addition Wesley, Reading, MA, 1989
2 J. Kennedy and R. Eberhart, "Particle swarm optimization," Proceedings of IEEE Int. Conf. Neural Networks, vol. 4, Perth, Australia, 1995, pp. 1942-1948
3 Z. Michalewicz, "Genetic Algorithms + Data structures = Evolutionary Programs", Springer, 1996
4 T. Yalcinoz and M. J. Short, "Neural networks approach for solving economic dispatch problem with transmission capacity constraints," IEEE Trans. Power Systems, vol. 13, no. 2, pp. 307-313, May 1998   DOI   ScienceOn
5 W. M. Lin, F. S. Cheng and M. T. Say, "An improved tabu search for economic dispatch with multiple minima," IEEE Trans. Power Systems, vol. 17, no. 1, pp. 108-112, Feb. 2002   DOI   ScienceOn
6 N. Sinha, R. Chakrabarti and P. K. Chattopadhyay, "Evolutionary programming techniques for economic load dispatch," IEEE Trans. Evolutionary Com-putation, vol. 7, no. 1, pp. 83-94, Feb. 2003   DOI   ScienceOn
7 Z.-L. Gaing, "Particle swarm optimization to solving the economic dispatch considering the generator constraints," IEEE Trans. Power Systems, vol. 18, no. 3, pp. 1187-1195, Aug. 2003   DOI   ScienceOn
8 T. Yalcinoz, B. J. Cory and M. J. Short, "Hopfield neural network approaches to economic dispatch problems," International Journal of Electrical Power and Energy Systems, vol. 23, no. 6, pp. 435-442, Aug. 2001   DOI   ScienceOn
9 R. Naresh, J. Dubey and J. Sharma, "Two-phase neural network based modeling framework of constrained economic load dispatch," IEE Proceedings - Generation Transmission Distribution, vol. 151, no. 3, pp. 373-378, May 2004
10 C. L. Chen and S. C. Wang, "Branch and bound scheduling for thermal generating units," IEEE Trans. Energy Conversion, vol. 8, no. 2, pp. 184-189, June 1993   DOI   ScienceOn
11 K. P. Wong and C. C. Fung, "Simulated-annealing based economic dispatch algorithm," IEE Proceedings - Generation Transmission Distribution, vol. 140, no. 6, pp. 509-514, Nov. 1993
12 T. A. A. Victoire and A. E. Jeyakumar, "Discussion of particle swarm optimization to solving the economic dispatch considering the generator constraints," IEEE Trans. Power Systems, vol. 19, no. 4, pp. 2121-2123, Nov. 2004
13 F. N. Lee and A. M. Breiphol, "Reserve constrained economic dispatch with prohibited operating zones," IEEE Trans. Power Systems, vol. 8, no. 1, pp. 246-254, Feb. 1993   DOI   ScienceOn
14 J. Y. Fan and J. D. McDonald, "A practical approach to real time economic dispatch considering unit's prohibited operating zones," IEEE Trans. Power Systems, vol. 9, no. 4, pp. 1737-1743, Nov. 1994   DOI   ScienceOn
15 D. C. Walters and G. B. Sheble, "Genetic algorithm solution of economic dispatch with valve point loadings", IEEE Trans. Power Systems, vol. 8, no. 3, pp. 1325-1332, Aug. 1993   DOI   ScienceOn
16 H. T. Yang, P. C. Yang and C. L. Huang, "Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions," IEEE Trans. Power Systems, vol. 11, no. 1, pp. 112-118, Feb. 1996   DOI   ScienceOn
17 A. J. Wood and B. F. Wollenberg, Power generation, operation and control, New York: John Wiley Inc., 1984
18 K. Kirchmayer, Economic operation of power systems, New York: John Wiley & Sons, 1958
19 R. Bellman, Dynamic programming, Princeton University Press, 1957
20 Z. X. Liang and J. D. Glover, "A zoom feature for a dynamic programming solution to economic dispatch including transmission losses," IEEE Trans. Power Systems, vol. 7, no. 2, pp. 544-550, May 1992   DOI   ScienceOn
21 K.Y. Lee, "Fuel cost minimization for both real and reactive power dispatches," IEE Proceedings - Generation Transmission Distribution, vol. 131, no. 3, pp. 85-93, May 1984