Optimizing UPFC parameters via two swarm algorithms synergy

Author

Saadi, Slami ; Elaguab, Mohamed ; Guessoum, Abderrezak ; Bettayeb, Maamar

Author_Institution

Dept. of Sci. & Tech., Univ. Ziane, Djelfa, Algeria

fYear

2012

fDate

20-23 March 2012

Firstpage

1

Lastpage

6

Abstract

In this paper, a novel hybrid swarm intelligence optimization approach is proposed based on the synergy of Particle Swarm (PSO) and Bacterial Foraging (BFO) Optimization algorithms to determine the optimal parameters of the Unified Power Flow Controller (UPFC). The objective of hybridization is to reduce the convergence time while maintaining high accuracy. A comparison with the classical state feedback decoupling method shows better dynamic performance of the proposed approach in system behavior, stability and pursuit of real values to reference ones.

Keywords

convergence; load flow control; particle swarm optimisation; stability; UPFC parameters; bacterial foraging optimization algorithm; convergence time reduction; hybrid swarm intelligence optimization approach; hybridization; particle swarm optimization algorithm; stability; swarm algorithm synergy; unified power flow controller; Convergence; Hybrid power systems; Microorganisms; Modulation; Optimization; Reactive power; State feedback; BFO; Hybrid; PSO; UPFC; feedback decoupling;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals and Devices (SSD), 2012 9th International Multi-Conference on

Conference_Location

Chemnitz

Print_ISBN

978-1-4673-1590-6

Electronic_ISBN

978-1-4673-1589-0

Type

conf

DOI

10.1109/SSD.2012.6197927

Filename

6197927