INFORMATION CHANGE THE WORLD

International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.5, No.7, Jun. 2013

A Modified Particle Swarm Optimization Technique for Economic Load Dispatch with Valve-Point Effect

Full Text (PDF, 423KB), PP.32-41


Views:146   Downloads:8

Author(s)

Hardiansyah

Index Terms

Particle Swarm Optimization, Economic Load Dispatch, Non-Smooth Cost Functions, Valve-Point Effect

Abstract

This paper presents a new approach for solution of the economic load dispatch (ELD) problem with valve-point effect using a modified particle swarm optimization (MPSO) technique. The practical ELD problems have non-smooth cost function with equality and inequality constraints, which make the problem of finding the global optimum difficult when using any mathematical approaches. In this paper, a modified particle swarm optimization (MPSO) mechanism is proposed to deal with the equality and inequality constraints in the ELD problems through the application of Gaussian and Cauchy probability distributions. The MPSO approach introduces new diversification and intensification strategy into the particles thus preventing PSO algorithm from premature convergence. To demonstrate the effectiveness of the proposed approach, the numerical studies have been performed for three different test systems, i.e. six, thirteen and forty generating unit systems, respectively. The results shows that performance of the proposed approach reveal the efficiently and robustness when compared results of other optimization algorithms reported in literature.

Cite This Paper

Hardiansyah,"A Modified Particle Swarm Optimization Technique for Economic Load Dispatch with Valve-Point Effect", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.7, pp.32-41, 2013.DOI: 10.5815/ijisa.2013.07.05

Reference

[1]A. J Wood and B. F. Wollenberg, Power Generation, Operation, and Control, 2nd ed., John Wiley and Sons, New York, 1996.

[2]Z. X. Liang and J. D. Glover. A Zoom Feature for a Dynamic Programming Solution to Economic Dispatch Including Transmission Losses, IEEE Trans. on Power Systems, 1992, 7(2): 544-550.

[3]P. H. Chen and H. C. Chang. Large-Scale Economic Dispatch by Genetic Algorithm, IEEE Trans. Power Systems, 1995, 10(4): 1919-1926.

[4]C. L. Chiang. Improved Genetic Algorithm for Power Economic Dispatch of Units with Valve-Point Effects and Multiple Fuels, IEEE Trans. Power Systems, 2005, 20(4): 1690-1699.

[5]W. M. Lin, F. S. Cheng and M. T. Tsay. An Improved Tabu Search for Economic Dispatch with Multiple Minima, IEEE Trans. Power Systems, 2002, 17(1): 108-112.

[6]K. P. Wong and C. C. Fung. Simulated Annealing Based Economic Dispatch Algorithm, Proc. Inst. Elect. Eng. C, 1993, 140(6): 509-515.

[7]J. H. Park, Y. S. Kim, I. K. Eom and K. Y. Lee. Economic Load Dispatch for Piecewise Quadratic Cost Function using Hopfield Neural Network, IEEE Trans. Power Systems, 1993, 8(3): 1030-1038.

[8]K. Y. Lee, A. Sode-Yome and J. H. Park. Adaptive Hopfield Neural Network for Economic Load Dispatch, IEEE Trans. Power Systems, 1998, 13(2): 519-526.

[9]T. Jayabarathi and G. Sadasivam. Evolutionary Programming-Based Economic Dispatch for Units with Multiple Fuel Options, European Trans. Elect. Power, 2000, 10(3): 167-170.

[10]N. Sinha, R. Chakrabarti and P. K. Chattopadhyay. Evolutionary Programming Techniques for Economic Load Dispatch, IEEE Trans. Evolutionary Computation, 2003, 7(1): 83-94.

[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, 1996, 11(1): 112-118. 

[12]J. Kennedy and R. Eberhart. Particle Swarm Optimization, in Proc. IEEE Int. Conf. Neural Networks (ICNN'95), Perth, Australia, 1995, IV: 1942-1948.

[13]Y. Shi and R. Eberhart. A Modified Particle Swarm Optimizer, Proceedings of IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, 1998, 69-73.

[14]Z. L. Gaing. Particle Swarm Optimization to Solving the Economic Dispatch Considering the Generator Constraints, IEEE Trans. Power Systems, 2003, 18(3): 1187-1195.

[15]J. B. Park, K. S. Lee, J. R. Shin and K. Y. Lee. A Particle Swarm Optimization for Economic Dispatch with Non-Smooth Cost Functions, IEEE Trans. Power Systems, 2005, 20(1): 34-42.

[16]J. B. Park, Y. W. Jeong, J. R. Shin, K. Y. Lee and J. H. Kim. A Hybrid Particle Swarm Optimization Employing Crossover Operation for Economic Dispatch Problems with Valve-Point Effects, Engineering Intelligent Systems for Electrical Engineering and Communications, 2007, 15(2): 29-34.

[17]Shi Yao Lim, Mohammad Montakhab and Hassan Nouri. Economic Dispatch of Power System Using Particle Swarm Optimization with Constriction Factor, International Journal of Innovations in Energy Systems and Power, 2009, 4(2): 29-34.

[18]L. S. Coelho and C.S. Lee. Solving Economic Load Dispatch Problems in Power Systems Using Chaotic and Gaussian Particle Swarm Optimization Approaches, Electric Power and Energy Systems, 2008, 30: 297-307.

[19]A. I. Selvakumar and K. Thanushkodi. A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems, IEEE Trans. Power Systems, 2007, 22(1): 42–51.

[20]S. Muthu Vijaya Pandian and K. Thanushkodi. An Evolutionary Programming Based Efficient Particle Swarm Optimization for Economic Dispatch Problem with Valve-Point Loading, European Journal of Scientific Research, 2011, 52(3): 385-397. 

[21]C.H. Chen and S. N. Yeh. Particle Swarm Optimization for Economic Power Dispatch with Valve-Point Effects, IEEE PES Transmission and Distribution Conference and Exposition Latin America, Venezuela, 2006.