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research article

Realistic Wind Farm Layout Optimization through Genetic Algorithms Using a Gaussian Wake Model

Kirchner Bossi, Nicolas  
•
Porté-Agel, Fernando  
December 1, 2018
Energies

Wind Farm Layout Optimization (WFLO) can be useful to minimize power losses associated with turbine wakes in wind farms. This work presents a new evolutionary WFLO methodology integrated with a recently developed and successfully validated Gaussian wake model (Bastankhah and Porte-Agel model). Two different parametrizations of the evolutionary methodology are implemented, depending on if a baseline layout is considered or not. The proposed scheme is applied to two real wind farms, Horns Rev I (Denmark) and Princess Amalia (the Netherlands), and two different turbine models, V80-2MW and NREL-5MW. For comparison purposes, these four study cases are also optimized under the traditionally used top-hat wake model (Jensen model). A systematic overestimation of the wake losses by the Jensen model is confirmed herein. This allows it to attain bigger power output increases with respect to the baseline layouts (between 0.72% and 1.91%) compared to the solutions attained through the more realistic Gaussian model (0.24-0.95%). The proposed methodology is shown to outperform other recently developed layout optimization methods. Moreover, the electricity cable length needed to interconnect the turbines decreases up to 28.6% compared to the baseline layouts.

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energies-11-03268.pdf

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Publisher's Version

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http://purl.org/coar/version/c_970fb48d4fbd8a85

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openaccess

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CC BY

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4.79 MB

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Adobe PDF

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0fedbabe492f0eb194ccb4d7911e4eaf

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