Title :
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
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;
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
DOI :
10.1109/CEC.2008.4630964
