DocumentCode :
666037
Title :
A clustering approach for the wind turbine micro siting problem through genetic algorithm
Author :
Rodrigues, S. ; Bauer, Pavol ; Pierik, Jan
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
1938
Lastpage :
1943
Abstract :
Offshore wind farms with high installed capacities and located further from the shore are starting to be built by northern European countries. Furthermore, it is expected that by 2020, several dozens of large offshore wind farms (LOWFs) will be built in the Baltic, Irish and North seas. These LOWFs will be constituted of a considerable amount of wind turbines (WTs) packed together. Due to shadowing effects between turbines, the power production is reduced, resulting in a decreased wind farm efficiency. Hence, when LOWFs are considered, wake losses reduction is an important optimization goal that needs to be considered. This work presents a clustering approach to optimize the energy production of LOWFs through a genetic algorithm (GA). The method consists of a turbine clustering strategy where the optimal wind farm layout is obtained in different steps. The number of turbines used in each step is increased until all turbine locations have been optimized. The results demonstrate the method effectiveness. A computational time decrease and a reduction of the problem search space are observed when compared to the standard optimization strategy, without jeopardizing the quality of the optimal layouts achieved.
Keywords :
genetic algorithms; losses; offshore installations; search problems; statistical analysis; wakes; wind power plants; wind turbines; LOWF; energy production optimization; genetic algorithm; large offshore wind farms; optimal wind farm layout; power production reduction; problem search space; shadowing effects; wake losses reduction; wind turbine clustering strategy; wind turbine micro siting problem; Genetic algorithms; Layout; Optimization; Wind farms; Wind speed; Wind turbines; Genetic Algorithm; Offshore Wind Energy; Turbine Clustering; Turbine Siting; Wake Losses; Wind Farm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
ISSN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2013.6699428
Filename :
6699428
Link To Document :
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