Optimal harmonic estimation Using Dynamic Bacterial Swarming Algorithm

Author

Li, M.S. ; Ji, T.Y. ; Lu, Z. ; Wu, Henry

Author_Institution

Dept. of Electr. Eng. & Electron., Univ. of Liverpool, Liverpool

fYear

2008

fDate

1-6 June 2008

Firstpage

1302

Lastpage

1308

Abstract

This paper presents a dynamic bacterial swarming algorithm (DBSA) for harmonic estimation in dynamic environment. DBSA is designed from a dynamic searching framework that combines the underlying mechanisms of bacterial chemotaxis, quorum sensing and environment adaptation. The harmonic estimation process utilizes DBSA to estimate the phases of the harmonics, alongside a least square (LS) method to estimate the amplitudes. A cost function is given as an error between the original signal and the reconstructed signal.

Keywords

amplitude estimation; particle swarm optimisation; phase estimation; power system harmonics; search problems; signal reconstruction; amplitudes estimation; bacterial chemotaxis; cost function; dynamic bacterial swarming algorithm; dynamic searching framework; environment adaptation; least square method; optimal harmonic estimation; phases estimation; power system; quorum sensing; signal reconstruction; Amplitude estimation; Discrete Fourier transforms; Frequency estimation; Heuristic algorithms; Microorganisms; Parameter estimation; Phase estimation; Pollution; Power harmonic filters; Power system harmonics; Dynamic bacterial swarming algorithm; Harmonic estimation; Optimization; Power system;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-1822-0

Electronic_ISBN

978-1-4244-1823-7

Type

conf

DOI

10.1109/CEC.2008.4630964

Filename

4630964