Power System Reactive Power Optimization Based on Adaptive Particle Swarm Optimization Algorithm

Author

Li, Yang ; Gao, Liqun ; Zhang, Junzheng ; Yang Li

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang

Volume

2

fYear

0

fDate

0-0 0

Firstpage

7572

Lastpage

7576

Abstract

Aiming at the precocious convergence problem of particle swarm optimization algorithm, adaptive particle swarm optimization (APSO) algorithm was presented. In this algorithm, inertia weight was nonlinearly adjusted by using population diversity information. Velocity mutation operator and position crossover operator were both introduced and the global performance was clearly improved. The algorithm had been applied to reactive power optimization. The simulation results of the standard IEEE-30-bus power system had indicated that APSO was able to undertake global search with a fast convergence rate and a feature of robust computation. It was proved to be efficient and practical during the reactive power optimization

Keywords

IEEE standards; particle swarm optimisation; power systems; reactive power; IEEE-30-bus power system; adaptive mutation; adaptive particle swarm optimization; convergence problem; population diversity information; position crossover operator; power system reactive power optimization; velocity mutation operator; Ant colony optimization; Convergence; Dynamic programming; Genetic mutations; Linear programming; Particle swarm optimization; Power system modeling; Power systems; Reactive power; Voltage; adaptive mutation; particle swarm optimization; reactive power optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713438

Filename

1713438