DocumentCode :
22014
Title :
A New and Efficient Method for Optimal Design of Large Offshore Wind Power Plants
Author :
Serrano Gonzalez, Javier ; Burgos Payan, Manuel ; Riquelme Santos, Jesus
Author_Institution :
Dept. of Electr. Eng., Univ. of Seville, Seville, Spain
Volume :
28
Issue :
3
fYear :
2013
fDate :
Aug. 2013
Firstpage :
3075
Lastpage :
3084
Abstract :
This work addresses the problem of the optimal micro-siting of the wind turbines in large offshore wind power plants with the aim of maximizing the economic profitability of the project. To achieve this goal it is first necessary to estimate the required investment and, secondly, the yearly operation and maintenance costs as well as the yearly income resulting from the operation of the wind power plant over its life span. With this purpose, a complete and realistic model of economic behavior for offshore wind farms has been developed. The optimal turbines layout of a wind farm is a challenge both from a mathematical and technological point of view. The size of the solution space (computational complexity) of the problem addressed in this work dramatically increases with an increase in size of the wind farm. In order to address this difficulty, a new and computationally efficient algorithm is proposed. The method is based in the division of available marine plot in smaller areas of suitable size, sequentially optimized by an improved genetic algorithm.
Keywords :
genetic algorithms; maintenance engineering; mathematical analysis; offshore installations; power generation economics; profitability; wind power plants; economic behavior; economic profitability; genetic algorithm; investment; large offshore wind power plants; maintenance costs; marine plot; mathematical analysis; optimal design; optimal micrositing; optimal turbines layout; wind turbines; Genetic algorithm; micro-siting; offshore wind farm; wake effect;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2013.2251014
Filename :
6502287
Link To Document :
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