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Application of Chaotic Particle Swarm Optimization for Solving Economic Dispatch Problems with Non-convex Cost Function

A. Rajapandiyan, M. Alex

Abstract


One of the significant optimization troubles concerning power system issues is to find out and afford an economic condition for generation units based on the generation and transmission line constraints, which is called Economic Dispatch (ED). The nonlinearity of the present troubles builds conventional mathematical methods incapable to offer a speedy and vigorous solution, mainly when the power system holds large number of generation units. This paper presents an efficient approach for solving economic dispatch (ED) problems with non-convex cost functions under variable load conditions using chaotic particle swarm optimization (CPSO) to find fast and efficient solutions for different power systems with different generation unit numbers. This paper proposes an chaotic PSO framework employing chaotic sequences combined with the conventional linearly decreasing inertia weights and adopting a crossover operation scheme to increase both exploration and exploitation functionality of the PSO. The proposed CPSO is implemented to three special non-convex ED problems with valve-point effects, prohibited operating zones with ramp rate limits as well as transmission community losses, and multi-fuels with valve-factor outcomes. The outcomes reveal that the proposed set of rules is able to attaining a better first-rate solution together with mathematical simplicity, rapid convergence, and robustness to cope with the non-linearity of economic load dispatch hassle.


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References


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