A hybrid PBIL-based Harmony Search method with application in wind generator optimization

Author

Gao, X.Z. ; Jokinen, T. ; Wang, X. ; Ovaska, S.J. ; Arkkio, A.

Author_Institution

Dept. of Electr. Eng., Aalto Univ., Aalto, Finland

fYear

2010

fDate

15-17 Dec. 2010

Firstpage

261

Lastpage

267

Abstract

The Harmony Search (HS) method is a popular meta-heuristic optimization algorithm, which has been extensively employed to handle various engineering problems. However, it sometimes fails to offer a satisfactory convergence performance. In this paper, we propose and study a hybrid HS approach, HS-PBIL, by merging the HS together with the Population-Based Incremental Learning (PBIL). Numerical simulations demonstrate that our HS-PBIL is well capable of outperforming the regular HS method in attacking a practical wind generator optimization problem.

Keywords

AC generators; heuristic programming; learning (artificial intelligence); power engineering computing; search problems; wind power plants; hybrid HS approach; hybrid PBIL-based harmony search method; meta-heuristic optimization algorithm; numerical simulations; population-based incremental learning; wind generator optimization problem; Harmony Search (HS); Population-Based Incremental Learning (PBIL); hybrid optimization methods; wind generator optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on

Conference_Location

Fukuoka

Print_ISBN

978-1-4244-7377-9

Type

conf

DOI

10.1109/NABIC.2010.5716283

Filename

5716283