A Hybrid Genetic Algorithm Approach for Optimal Power Flow

Autor:	Sydulu Maheswarapu, Mithun M. Bhaskar M. Bhaskar
Rok vydání:	2011
Předmět:	Mathematical optimization Engineering Meta-optimization business.industry Population-based incremental learning Particle swarm optimization Power flow Differential evolution Genetic algorithm Convergence (routing) Harmony search Electrical and Electronic Engineering business Algorithm
Zdroj:	TELKOMNIKA (Telecommunication Computing Electronics and Control). 9:211
ISSN:	2302-9293 1693-6930
DOI:	10.12928/telkomnika.v9i2.689
Popis:	This paper puts forward a reformed hybrid genetic algorithm (GA) based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA), adaptive genetic algorithm (AGA), differential evolution (DE), particle swarm optimization (PSO) and music based harmony search (MBHS) on a IEEE30 bus test bed, with a total load of 283.4 MW. It’s found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::fd8ee77453925d2bea37f406391ed25d https://doi.org/10.12928/telkomnika.v9i2.689 Zobrazit plný text záznamu Plný text ve formátu PDF