Meta heuristic search algorithms for short-term hydrothermal scheduling

Proceedings of the 2006 International Conference on Machine Learning and Cybernetics

Volumn 2006, Issue , 2006, Pages 4050-4056

  Sinha, Nidul ^a   Lai, Loi Lei ^b  

^a NATIONAL INSTITUTE OF TECHNOLOGY SILCHAR   (India)

^b CITY UNIVERSITY   (United Kingdom)

Author keywords

Fast evolutionary programming; Hydro thermal scheduling; Particle swarm optimization

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; GLOBAL OPTIMIZATION; PROBLEM SOLVING;

FAST EVOLUTIONARY PROGRAMMING; HYDRO-THERMAL SCHEDULING; PARTICLE SWARM OPTIMIZATION;

HEURISTIC ALGORITHMS;

EID: 33947273181     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLC.2006.258860     Document Type: Conference Paper

References (28)

1. Wood, A.J. and Wollenberg, B.F.: Power Generation, Operation and Control, John Wiley and Sons, New York, 1984.
2. Kirchmayer, L.K. : Economic Control of Interconnected Systems, JohnWiley and Sons, New York, 1959.
3. Nilson, O. and Sjelvgren, D. : "Mixed integer programming applied toshort-term planning of a hydro-thermal system", Proc. of the 1995 IEEE PICA, Salt Lake City, Utah, USA, May,1995,pp.158-163.
4. Engles, L., Larson, R. E., Peschon, J. and Stanton, K. N. : "Dynamic pr-ogramming applied to hydro and thermal generation scheduling" in IEEE tutorial course text, 76CH1107-2-PWR,IEEE, New York, 1976.
5. Jimenez, N.R. and Conejo, A.J.: "Short-term hydrothermal coordination by Lagrangian relaxation: Solution to the dual problem", in IEEE-PES Winter Meeting, Orlando, FL,USA, 1998, paper PE-333 PWRS-0-12-1997.
6. Habibollahzadeh, H. and Bubenko, J.A.: " Application of decomposition techniques to short-term operation planning of hydrothermal power system", IEEE Trans. on Power Systems, Vol.PWRS-I,No.1,Feb,1986,pp.41-47.
7. Carvalho, M.F. and Soares, S.: " An efficient hydro-thermal scheduling algorithm", IEEE Trans., Vol.PWRS-4, 1987,pp.537-542.
8. Wong, K.P. and Wong, Y.W.: "Short-term hydrothermal scheduling, part-I: Simulated annealing approach", IEE Proc., Part-C, Vol.141, No. 5, Sept., 1994,pp.497-501.
9. Wu, Y.-G., Ho, C.-Y. and Wang, D.-Y.: " A diploid genetic approach to short-term scheduling of hydro-thermal system", IEEE Trans. on Power Systems, vol.15, no.4, November,2000, pp. 1268-1274.
10. Th. Bäck and H.-P. Schwefel: " An overview of evolutionary algorithms for parameter optimization", Evolutionary Computation, Vol.1, No.1,1993,pp.1-23.
11. Fogel, D.B. : " An introduction to simulated evolutionary optimization", IEEE Transactions on Neural Networks, Vol.5, No.1,1994, pp.3-14.
12. Yao, X., Liu, Y. and Lin, G. : " Evolutionary Programming made faster", IEEE Transactions on Evolutionary Computation, Vol.3, No.2, July, 1999, pp.82-102.
13. Fogel, D.B. : "A comparison of evolutionary programming and genetic algorithms on selected constrained optimization problems", Simulation, June,1995,pp.397-404.
14. Yang, P.-C., Yang, H.-T. and Huang, C.-L.: " Scheduling short-term hydrothermal generation using evolutionary programming techniques", IEE Proc., Gener. Transm. Distrib., Vol.143, No.4, July,1996, pp.371-376.
15. Hota, P.K., Chakrabarti, R. and Chattopadhyay, P.K.: " Short-term hydrothermal scheduling through evolutionary programming technique", EPSR, Vol.52, No.2, November 1,1999, pp.189-196.
16. Sinha, N., Chakrabarti, R. and Chattopadhyay, P.K.: " Evolutionary programming techniques for economic load dispatch", paper submitted to IEEE Trans. on Evolutionary Computation.
17. Sinha, Nidul, Chakrabarti, R. and Chattopadhyay, P. K.: "Fast Evolutionary programming techniques for short-term hydrothermal scheduling", IEEE transactions on Power Systems, Vol.18, No.1, February, 2003, pp.214-220.
18. Sinha, Nidul, Chakrabarti, R. and Chattopadhyay, P. K.: "Fast Evolutionary programming techniques for short-term hydrothermal scheduling", EPSR, EPSR, Vol. 66, Issue 2, August 2003, pages 97-103.
19. Fogel, D.B. : " Evolutionary computation: Toward a new philosophy of machine intelligence", IEE Press, Piscataway, NJ (1995).
20. [Fogel L.J., Owens A.J. and Walsh M.J. : "Artificial intelligence through simulated evolution", John Wiley, NY, 1966.
21. Yao, X. and Liu, Y. : "Fast evolutionary programming", Proc. Of the Fifth Annual Conference on Evolutionary Programming, Cambridge, MA, The MIT Press, 1996, pp.451-460.
22. Chellapilla, K. and Fogel, D. B. : " Two new mutation operators for enhanced search and optimization in evolutionary programming", SPIE's International Symposium on Optical Science, Engineers and Instrumentation Conference, 3165: Applications of Soft Computing, SPIE Press, pp.260-269.
23. Kennedy, J., and Eberhart, R.: "Particle Swarm Optimization," Proceedings of IEEE International Conference on Neural Netwroks, Vol. IV, pp. 1942-1948, Perth, Australia, 1995.
24. Shi, Y. and Eberhart, R.: "A Modified Particle Swarm Optimizer," Proceedings of IEEE International Conference on Evolutionary Computation, pp. 69-73, Anchorage, May 1998.
25. Shi, Y., and Ebcrhart, R.: "Empirical Study of Particle Swarm Optimization," Proceedings of the 1999 Congress on Evolutionary Computation, pp. 1945-1950, Piscataway, 1999.
26. El-Gallad, A., El-Hawary, M., Sallam, A., and Kalas, A.: "Particle swarm optimizer for constrained economic dispatch with prohibited operating zones." Proc. IEEE Candian Conf. On Electrical and Computer Engineering, 2002, pp.78-81.
27. Naka, S., Genji, T., Yura, T., and Fukuyama, Y.: "Practical distribution state estimation using hybrid particle swarm optimization," Proc. IEEE Power Eng. Soc. Winter Meeting, vol. 2, pp. 815-820, 2001.
28. Houck, C. R., Joines, J. A., and Kay, M. G. (1995): "A genetic algorithm for function optimization: A Matlab implementation". Technical Report NCSU-IE TR 95-09, North Carolina State University. Also available as http://www.fmmcenter.ncsu.edu/facstaff/joines/papers/gaot.ps.