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Commercial wind farm layout design a...

Chen, Ying.

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Commercial wind farm layout design and optimization.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Commercial wind farm layout design and optimization./
Author:	Chen, Ying.
Description:	46 p.
Notes:	Source: Masters Abstracts International, Volume: 52-01.
Contained By:	Masters Abstracts International52-01(E).
Subject:	Engineering, Industrial. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1540736
ISBN:	9781303211348

Commercial wind farm layout design and optimization.
Chen, Ying.

Commercial wind farm layout design and optimization. - 46 p.

Source: Masters Abstracts International, Volume: 52-01.

Thesis (M.S.)--Texas A&M University - Kingsville, 2013.

To increase the power output or decrease of cost consumption of a wind farm, layout optimization has become a critical method to realize this goal. The past research has already applied intelligent algorithms to optimizing the layout of a wind farm under wind conditions such as single wind speed and wind direction, single wind speed and multiple wind direction and multiple wind speeds and multiple wind directions. However, these wind conditions are all simplified ones and are not suitable for building up a commercial wind farm. In this study, first the author builds up a cost model based on the real wind farms located in Texas and sets up a wind condition model on the basis of local wind condition within a month. After this, the author focuses on the commercial wind farm layout optimization model (CWFLO) based on genetic algorithm. Current commercial wind turbine types and their corresponding hub heights are the objects of optimization with their positions. Four case studies are conducted to investigate: 1. how many wind turbines are actually needed in the given wind farm; 2: how to optimize the layout of an irregular shape wind farm; 3: how to improve the current optimization method; 4: What difference will appear for the layout when changing the cost model. The results achieved clearly demonstrate that this new optimization method is able to improve the fitness value of the objective functions.

ISBN: 9781303211348Subjects--Topical Terms:

626639
Engineering, Industrial.

Commercial wind farm layout design and optimization.
LDR:02327nam 2200289 4500 001 1957514
005 20140106101254.5
008 150210s2013 ||||||||||||||||| ||eng d
020 $a 9781303211348
035 $a (UMI)AAI1540736
035 $a AAI1540736
040 $a UMI $c UMI
100 1 $a Chen, Ying. $3 1058964
245 1 0 $a Commercial wind farm layout design and optimization.
300 $a 46 p.
500 $a Source: Masters Abstracts International, Volume: 52-01.
500 $a Adviser: Hua Li.
502 $a Thesis (M.S.)--Texas A&M University - Kingsville, 2013.
520 $a To increase the power output or decrease of cost consumption of a wind farm, layout optimization has become a critical method to realize this goal. The past research has already applied intelligent algorithms to optimizing the layout of a wind farm under wind conditions such as single wind speed and wind direction, single wind speed and multiple wind direction and multiple wind speeds and multiple wind directions. However, these wind conditions are all simplified ones and are not suitable for building up a commercial wind farm. In this study, first the author builds up a cost model based on the real wind farms located in Texas and sets up a wind condition model on the basis of local wind condition within a month. After this, the author focuses on the commercial wind farm layout optimization model (CWFLO) based on genetic algorithm. Current commercial wind turbine types and their corresponding hub heights are the objects of optimization with their positions. Four case studies are conducted to investigate: 1. how many wind turbines are actually needed in the given wind farm; 2: how to optimize the layout of an irregular shape wind farm; 3: how to improve the current optimization method; 4: What difference will appear for the layout when changing the cost model. The results achieved clearly demonstrate that this new optimization method is able to improve the fitness value of the objective functions.
590 $a School code: 1187.
650 4 $a Engineering, Industrial. $3 626639
690 $a 0546
710 2 $a Texas A&M University - Kingsville. $b Mechanical and Industrial Engineering. $3 2092433
773 0 $t Masters Abstracts International $g 52-01(E).
790 1 0 $a Li, Hua, $e advisor
790 1 0 $a Jin, Kai $e committee member
790 1 0 $a Elkassabgi, Yousri Elkassabgi $e committee member
790 $a 1187
791 $a M.S.
792 $a 2013
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1540736