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An Improved Dynamic Programming Approach to Economic Power Dispatch with Generator Constraints and Transmission Losses
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 Title & Authors
An Improved Dynamic Programming Approach to Economic Power Dispatch with Generator Constraints and Transmission Losses
Balamurugan, R.; Subramanian, S.;
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 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;
 Language
English
 Cited by
 References
1.
A. J. Wood and B. F. Wollenberg, Power generation, operation and control, New York: John Wiley Inc., 1984

2.
K. Kirchmayer, Economic operation of power systems, New York: John Wiley & Sons, 1958

3.
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 crossref(new window)

4.
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

5.
R. Bellman, Dynamic programming, Princeton University Press, 1957

6.
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 crossref(new window)

7.
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 crossref(new window)

8.
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 crossref(new window)

9.
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 crossref(new window)

10.
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 crossref(new window)

11.
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 crossref(new window)

12.
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

13.
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 crossref(new window)

14.
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 crossref(new window)

15.
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

16.
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 crossref(new window)

17.
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 crossref(new window)

18.
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

19.
J. Kennedy and R. Eberhart, "Particle swarm optimization," Proceedings of IEEE Int. Conf. Neural Networks, vol. 4, Perth, Australia, 1995, pp. 1942-1948

20.
Z. Michalewicz, "Genetic Algorithms + Data structures = Evolutionary Programs", Springer, 1996

21.
D.E. Goldberg, "Genetic algorithm in search, optimization and machine learning", Addition Wesley, Reading, MA, 1989