DOI QR코드

DOI QR Code

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)
  • 발행 : 2008.09.30

초록

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.

키워드

참고문헌

  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 https://doi.org/10.1109/60.222703
  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 https://doi.org/10.1109/59.141757
  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 https://doi.org/10.1109/59.221233
  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 https://doi.org/10.1109/59.331425
  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 https://doi.org/10.1109/59.260861
  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 https://doi.org/10.1109/TEVC.2002.806788
  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 https://doi.org/10.1109/59.485992
  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 https://doi.org/10.1109/59.982200
  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 https://doi.org/10.1109/TPWRS.2003.814889
  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 https://doi.org/10.1109/59.667341
  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 https://doi.org/10.1016/S0142-0615(00)00084-3
  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

피인용 문헌

  1. Hybrid PSO-ACO technique to solve multi-constraint economic load dispatch problems for 6-generator system vol.38, pp.2-3, 2016, https://doi.org/10.1080/1206212X.2016.1218241