Optimizing UPFC parameters via two swarm algorithms synergy

Autor:	Mohamed Elaguab, Slami Saadi, Maamar Bettayeb, Abderrezak Guessoum
Rok vydání:	2012
Předmět:	Engineering Mathematical optimization business.industry Control theory Unified power flow controller Convergence (routing) Stability (learning theory) Particle swarm optimization Decoupling (cosmology) State (computer science) AC power Multi-swarm optimization business
Zdroj:	SSD
DOI:	10.1109/ssd.2012.6197927
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::729d9089b91f93b21a52951064a1fd92 https://doi.org/10.1109/ssd.2012.6197927 Zobrazit plný text záznamu