Different approaches of applying single-objective binary genetic algorithm on the wind farm design

Wang, Longyan, Kan, Man Shan, Shahriar, Md Rifat, & Tan, Andy C.C. (2014) Different approaches of applying single-objective binary genetic algorithm on the wind farm design. In World Congress on Engineering Asset Management 2014, 28-31 October 2014, Pretoria, South Africa. (Unpublished)


This paper discusses three different ways of applying the single-objective binary genetic algorithm into designing the wind farm. The introduction of different applications is through altering the binary encoding methods in GA codes. The first encoding method is the traditional one with fixed wind turbine positions. The second involves varying the initial positions from results of the first method, and it is achieved by using binary digits to represent the coordination of wind turbine on X or Y axis. The third is the mixing of the first encoding method with another one, which is by adding four more binary digits to represent one of the unavailable plots. The goal of this paper is to demonstrate how the single-objective binary algorithm can be applied and how the wind turbines are distributed under various conditions with best fitness. The main emphasis of discussion is focused on the scenario of wind direction varying from 0° to 45°. Results show that choosing the appropriate position of wind turbines is more significant than choosing the wind turbine numbers, considering that the former has a bigger influence on the whole farm fitness than the latter. And the farm has best performance of fitness values, farm efficiency, and total power with the direction between 20°to 30°.

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ID Code: 84829
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Wind farm layout, Optimization, Binary genetic algorithm
Divisions: Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Past > Institutes > Institute for Sustainable Resources
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 The Author(s)
Deposited On: 16 Jun 2015 22:38
Last Modified: 16 Jun 2015 22:38

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