Wind turbine micrositing by using the firefly algorithm

被引：28

作者：

Massan, Shafiq-ur-Rehman ^{[1
]}

Wagan, Asim Imdad ^{[2
]}

Shaikh, Muhammad Mujtaba ^{[3
]}

Abro, Riazuddin ^{[4
]}

机构：

[1] Shaheed Zulfikar Ali Bhutto Inst Sci & Technol, Karachi 75500, Pakistan

[2] DHA Suffa Univ, Dept Elect Engn, Karachi, Pakistan

[3] Mehran Univ Engn & Technol, Dept Basic Sci & Related Studies, Jamshoro, Pakistan

[4] Pakistan Council Sci & Ind Res, Inst Ind Elect Engn, Karachi, Pakistan

来源：

APPLIED SOFT COMPUTING | 2015年 / 27卷

关键词：

Wake function; Jensen wake model; Nature inspired algorithms; Firefly algorithm (FA); Genetic algorithms (GA); Wind turbines; OPTIMIZATION;

D O I：

10.1016/j.asoc.2014.09.048

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Traditionally energy has been a burning issue of mankind, however, this trend has changed with the advent of clean technologies such as wind power. It is common knowledge that wind turbines need to be installed in an open, unobstructed area to obtain the maximal power output. This document attempts to solve the problem of optimization of the layout of large wind farms by the use of nature inspired algorithms. Particular reference is made to the use of the firefly algorithm. A good comparison is made with the past approaches of the use of spread sheets and GA's for optimization. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：450 / 456

页数：7

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