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Implementing particle swarm optimization to solve economic load dispatch problem

Zaraki, Abolfazl and Othman, Mohd Fauzi Bin 2009. Implementing particle swarm optimization to solve economic load dispatch problem. Presented at: International Conference of Soft Computing and Pattern Recognition 2009, Malacca, Malaysia, 4-9 December 2009. 2009 International Conference of Soft Computing and Pattern Recognition. IEEE, pp. 60-65. 10.1109/SoCPaR.2009.24

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Abstract

Economic Load Dispatch (ELD) is one of an important optimization tasks which provides an economic condition for a power systems. In this paper, Particle Swarm Optimization (PSO) as an effective and reliable evolutionary based approach has been proposed to solve the constraint economic load dispatch problem. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. In this paper, a piecewise quadratic function is used to show the fuel cost equation of each generation units, and the B-coefficient matrix is used to represent transmission losses. The feasibility of the proposed method to show the performance of this method to solve and manage a constraint problems is demonstrated in 4 power system test cases, consisting 3,6,15, and 40 generation units with neglected losses in two of the last cases. The obtained PSO results are compared with Genetic Algorithm (GA) and Quadratic Programming (QP) base approaches. These results prove that the proposed method is capable of getting higher quality solution including mathematical simplicity, fast convergence, and robustness to solve hard optimization problems.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Engineering
Publisher: IEEE
ISBN: 9781424453306
Last Modified: 18 Mar 2020 12:00
URI: http://orca.cf.ac.uk/id/eprint/129004

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