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Solving the Economic Dispatch Problem by Using Differential Evolution

Authors: S. Khamsawang, S. Jiriwibhakorn


This paper proposes an application of the differential evolution (DE) algorithm for solving the economic dispatch problem (ED). Furthermore, the regenerating population procedure added to the conventional DE in order to improve escaping the local minimum solution. To test performance of DE algorithm, three thermal generating units with valve-point loading effects is used for testing. Moreover, investigating the DE parameters is presented. The simulation results show that the DE algorithm, which had been adjusted parameters, is better convergent time than other optimization methods.

Keywords: Differential evolution, Economic dispatch problem, Valve-point loading effect, Optimization method.

Digital Object Identifier (DOI):

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[1] A.J Wood and B.F. Wollenberg, "Power generation operation and control", John Wiley and Sons, New York, 1984.
[2] B. H. Chowdhury and S. Rahman, "A review of recent advances in economic dispatch," IEEE Trans. Power Syst, vol. 5, no. 4, pp. 1248- 1259, 1990.
[3] 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 Syst, vol. 11, no. 1, pp. 112-118, 1996.
[4] A. Immanuel Selvakumar and K. Thanushkodi, "A new particle swarm optimization solution to nonconvex economic dispatch problem," IEEE Trans. Power Syst, vol. 22, no. 1, pp. 42-51, 2007.
[5] W.M. Lin, F.S. Cheng and M.T. Tsay, "Improved tabu search for economic dispatch with multiple minima," IEEE Trans. Power Syst, vol. 17, no. 1, pp. 108-112, 2002.
[6] S. Khamsawang, C. Boonseng ans S. Pothiya, "Solving the economic dispatch problem with tabu search algorithm," In: Proceeding of the IEEE International Conference on Industrial Technology 2002, Bangkok, Thialand, pp. 274-278, 2002.
[7] Wong KP, Wong YW. "Genetic and Genetic/Simulated - Annealing approaches to economic dispatch," IEE Proc.Gener Transm. Distrib, vol. 141, no. 5, pp. 507-513, 1994.
[8] D.C. Walters and G. B. Sheble "Genetic algorithm solution of economic dispatch with valve point loading," IEEE Trans. Power Syst, vol. 8, no. 3, 1993.
[9] D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, MA: Addison-Wesley Publishing Company Inc., 1989.
[10] K.P. Wong 'Solving power system optimization problems using simulated annealing', Engng Applic. Artif.Intell. vol. 8, no. 6, pp. 665- 670, 1996.
[11] J.S. Al-Sumait, A.K AL-Othman and J.K. Sykulski, "Application of pattern search method to power system valve-piont economic dispacth", Int. J. Electr Power Energy Syst (2007), doi:10.1016/j.ijepes.2007.06.016
[12] N. Sinha, R. Chakrabarti and P.K. Chattopadhyay "Evolutionary programming techniques for economic load dispatch," IEEE Trans. Evol. Comput, vol. 7, no. 1, pp. 83-94, 2003.
[13] R. Storn and K.V. Price, "Differential evolution a simple and efficient heuristic for global optimization over continuous space," J. Global Optim, vol. 11, no. 4, pp. 341-359, 1997.
[14] K.V. Price, R.M. Storn, J.A. Lampinen, "Differential evolution; A practical approach to global optimization," Springer Berlin, Heidelberg, 2005.
[15] R. Storn, "System design by constraint adaptation and differential evolution," IEEE Trans. Evol. Comput, vol. 3, no. 1, pp. 22-34, 1999.
[16] D.T. Pham, A. Ghanbarzadeh, E. Koc, S. Otri, S. Rahim and M. Zaidi. "The bees algorithm, a novel tool for complex optimisation problems". Proc 2nd Int Virtual Conf. Intelligent Prod. Mach. and Syst, Oxford, Elsevier, pp.454-459, 2006.
[17] J.F. Kenedy and R.C. Eberhart, "particle swarm optimization," In: Proc IEEE international conference on neural networks, vol. 4, pp. 1942- 1948, 1995.
[18] M. Clerc and J.K. Kenedy, "The particle swarm: Explosion, stability and convergence in a multi - dimensional complex space," IEEE Trans. Evol. Comput, vol. 2, no. 3, pp. 91-96, 1998.