DocumentCode :
3301488
Title :
An improved evolutive algorithm for large offshore wind farm optimum turbines layout
Author :
Serrano Gonzalez, Javier ; Burgos Payan, Manuel ; Riquelme Santos, Jesus M.
Author_Institution :
Dept. of Electr. Eng., Univ. of Sevilla, Sevilla, Spain
fYear :
2011
fDate :
19-23 June 2011
Firstpage :
1
Lastpage :
6
Abstract :
A tool for optimal wind turbines location in large offshore wind farms is proposed. The algorithm objective is to optimize the profits given an investment on an offshore wind farm. Net Present Value (NPV) is used as a figure of the revenue in the proposed method. To estimate the NPV is necessary to calculate the initial capital investment and net cash flow during the offshore wind farm life cycle. The problem is an integer-mixed type problem, exhibits manifold optimal solutions (convexity) and some variables have a range of non allowed values (solutions space not simply connected). This fact makes the problem non-derivable, preventing the use of classical analytical optimization techniques. The proposed optimization algorithm is an improved evolutionary algorithm, for which crossover and mutation operations, specifics to the problem of micro positioning, have been developed.
Keywords :
evolutionary computation; integer programming; investment; offshore installations; power generation economics; wind turbines; analytical optimization techniques; improved evolutionary algorithm; initial capital investment; integer-mixed type problem; large offshore wind farm optimum turbines layout; net cash flow; net present value; offshore wind farm life cycle; Electricity; Investments; Optimization; Substations; Wind farms; Wind speed; Wind turbines; Evolutive algorithms; genetic algorithms; micrositing; offshore wind farm; optimization; wake effect;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech, 2011 IEEE Trondheim
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-8419-5
Electronic_ISBN :
978-1-4244-8417-1
Type :
conf
DOI :
10.1109/PTC.2011.6019366
Filename :
6019366
Link To Document :
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