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

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.