Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/27822
Title: Wind turbine layout optimization using multi-population genetic algorithm and a case study in Hong Kong offshore
Authors: Gao, X
Yang, H 
Lin, L
Koo, P
Keywords: Hong Kong offshore
Multi-population genetic algorithm
Wind farm
Wind turbine layout optimization
Issue Date: 2015
Publisher: Elsevier
Source: Journal of wind engineering and industrial aerodynamics, 2015, v. 139, p. 89-99 How to cite?
Journal: Journal of wind engineering and industrial aerodynamics 
Abstract: This paper proposes a multi-population genetic algorithm (MPGA) program for wind turbine layout optimization in a wind farm which aims at extracting the maximum power in a minimum investment cost. The MPGA program is applied to a 2km¡Ñ2km wind farm considering three different wind scenarios, i.e. (a): constant wind speed of 12m/s with fixed wind direction; (b): constant wind speed of 12m/s with variable wind direction and (c): variable wind speed of 8m/s, 12m/s, 17m/s with variable wind directions. Compared with previous studies, the results of power generation cost of energy and wind farm efficiency are improved in the paper using MPGA which validate that MPGA works effectively in wind turbine layout optimization with wind farm. Additionally, a case study of wind
URI: http://hdl.handle.net/10397/27822
ISSN: 0167-6105
EISSN: 1872-8197
DOI: 10.1016/j.jweia.2015.01.018
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