Solving Short Term Multi Chain Hydrothermal Scheduling Problem by Artificial Bee Colony Algorithm

Authors

  • S. M. Abdelmaksoud  Department of Electrical Engineering Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt
  • Ayman Y. Yousef  Department of Electrical Engineering Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt
  • H. A. Henry  Department of Electrical Engineering Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt

Keywords:

Hydrothermal Generation Scheduling, Artificial Bee Colony, Valve Point Loading Effect

Abstract

This paper presents an artificial bee colony algorithm for solving optimal short term hydrothermal scheduling problem. To demonstrate the effectiveness of the proposed algorithm, hydrothermal test system consists of three thermal units and four cascaded hydro power plants has been tested. The valve point loading effect is taken into consideration. In order to show the feasibility and robustness of the proposed algorithm, a wide range of thermal and hydraulic constraints are taken into consideration. The numerical results obtained by ABC algorithm are compared with those obtained from other methods such as genetic algorithm (GA), simulated annealing (SA), evolutionary programming (EP) and constriction factor based particle swarm optimization (CFPSO) technique to reveal the validity and verify the feasibility of the proposed method. The experimental results indicate that the proposed algorithm can obtain better schedule results with minimum execution time when compared to other methods.

References

  1. A. J. Wood and B.F. Wollenberg, "Power Generation, Operation, and Control", John Wiley and Sons., New York, 1984.
  2. D.P. Kothari and J.S. Dhillon, "Power system optimization", New Delhi, India, Pvt. Ltd, 2009.
  3. I.A. Farhat and M.E. El-Hawary, "Optimization methods applied for solving the short term hydro thermal coordination problem", Electric Power System Research, vol. 79, pp. 1308-1320, 2009
  4. J. Tang and P.B. Luh, "Hydro thermal scheduling via extended differential dynamic programming and mixed coordination", IEEE Trans. Power Syst., vol. 10, no. 4 pp. 2021-2028, Nov.,1995.
  5. Y. Jin-Shyr and C. Nanming, "Short term hydro thermal coordination using multi pass dynamic programming", IEEE Trans. Power Syst., vol. 4, pp. 1050-1056, 1989.
  6. X. Guan, E. Ni, R. Li and P.B. Luh, " An optimization based algorithm for scheduling hydro thermal power systems with cascaded reservoirs and discrete hydro constraints", IEEE Trans. Power Syst., vol. 12, pp. 1775-1780, 1997.
  7. S. Al-Agtash, "Hydro thermal scheduling by augmented lagrangian: consideration of transmission constraints and pumped storage units", Power Engineering Review, IEEE, vol. 21, pp. 58-59, 2001.
  8. O. Nilsson and D. Sjelvgren, "Mixed integer programming applied to short term planning of a hydro thermal system", IEEE Trans. Power Syst., vol. 11, pp. 281-286, 1996.
  9. L.M. Kimball, K.A. Clements, P.W. Davis and I. Nejdawi, "Multi period hydro thermal economic dispatch by an interior point method", Mathematical Problems in Engineering, vol. 8, pp. 33-42, 2002.
  10. J. Maturana, M-C. Riff," Solving the short-term electrical generation scheduling problem by an adaptive evolutionary approach", European Journal of Operational Research, vol. 179, pp. 677-691, 2007.
  11. N.C. Nayak and C.C.A. Rajan, "Hydro thermal scheduling by an evolutionary programming method with cooling-banking constraints", International Journal of Soft Computing and Engineering (IJSCE), Issue .3, vol. 2, pp. 517-521, July, 2012.
  12. D.P. Wong and Y.W. Wong, "Short term hydro thermal scheduling part. I. Simulated annealing approach", Generation, Transmission and Distribution, IEE Proceeding, vol. 141, pp. 497-501, 1994.
  13. D.N. Simopoulos, S.D. Kavatza and C.D. Vournas, "An enhanced peak shaving method for short term hydro thermal scheduling", Energy Conversion and Management, vol. 48, pp. 3018-3024, 2007.
  14. T. Jayabarathi, S. Chalasani and Z.A. Shaik, "Hybrid differential evolution and particle swarm optimization based solutions to short term hydro thermal scheduling", WSEAS Trans. Power Syst., Issue 11, vol. 2, Nov.,2007.
  15. V.N. Diew and W. Ongsakul, "Enhanced merit order and augmented lagrange Hopfield network for hydro thermal scheduling", International Journal of Electrical Power & Energy Systems, vol. 30, no. 2, pp. 93-101, 2008.
  16. M. Basu, "An interactive fuzzy satisfying method based on evolutionary programming technique for multi objective short-term hydro thermal scheduling", Electric Power Systems Research, vol. 69, pp. 277-285, 2004.
  17. E. Gil, J. Bustos, H. Rudnick," Short term hydrothermal generation scheduling model using genetic algorithm", IEEE Trans. Power Syst. vol. 18, no. 4, pp. 1256-1264, Nov., 2003.
  18. C.E. Zoumas, A.G. Bakirtzis, J.B. Theocharis, V. Petridis," A genetic algorithm solution approach to the hydro thermal coordination problem", IEEE Trans. Power Syst., vol. 19, no. 2, pp. 1356-1364, May, 2004.
  19. A. George, M.C. Reddy and A.Y. Sivaramakrishnan, "Short term hydro thermal scheduling based on multi-objective genetic algorithm", International Journal of Electrical Engineering, vol. 3, no. 1, pp. 13-26, 2010.
  20. G. Sreenivasan, C.H. Saibabu, S. Sivanagaraju," PSO based short-term hydrothermal scheduling with prohibited discharge zones", International Journal of Advanced Computer Science and Applications, vol. 2, no. 9, pp. 97-105, 2011.
  21. C. Sun and S. Lu, "Short term combined economic emission hydro thermal scheduling using improved quantum-behaved particle swarm optimization", Expert Syst. App., vol. 37, pp. 4232-4241, 2010.
  22. K.K. Mandal, M. Basu and N. Chakraborty, "Particle swarm optimization technique based short-term hydrothermal scheduling", Applied Soft Computing, pp. 1392-1399,2008.
  23. M.M. Salama, M.M. Elgazar, S.M. Abdelmaksoud and H.A. Henry, "Optimal generation scheduling of cascaded hydrothermal system using genetic algorithm and constriction factor based particle swarm optimization technique", International Journal of Scientific and Engineering Research, vol. 4, Issue 5, pp. 750-761, May, 2013.
  24. I.A. Farhat and M.E. El-Hawary, "Short-term hydro-thermal scheduling using an improved bacterial foraging algorithm", IEEE Electrical Power & Energy Conference, pp. 1-5, 2009.
  25. D. Karaboga and B. Akay, "A comparative study of artificial bee colony algorithm", Applied Mathematics and Computation, vol. 214 pp. 108-132, 2009.
  26. H.A. Shayanfar, E.S. Barazandeh, S.J. Seyed Shenava, A. Ghasemi and O. Abedinia, "A Solving optimal unit commitment by improved honey bee mating optimization", international Journal on Technical and Physical Problems of Engineering, vol. 4, no.4 pp. 38-45, Dec., 2012.
  27. J. Zhou, X. Liao, S. Ouyang, R. Zhang and Y. Zhang, "Multi-objective artificial bee colony algorithm for short-term hydrothermal system", Electrical Power and Energy Systems, vol. 55 pp. 542-553, 2014.

International Journal of Scientific Research in Science and Technology

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Published

2015-08-25

Issue

Volume 1, Issue 3, July-August-2015

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Research Articles

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How to Cite

[1]
S. M. Abdelmaksoud, Ayman Y. Yousef, H. A. Henry, " Solving Short Term Multi Chain Hydrothermal Scheduling Problem by Artificial Bee Colony Algorithm, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 1, Issue 3, pp.87-95, July-August-2015.