Maximizing the overall production of wind farms by setting the individual operating point of wind turbines
Javier Serrano González,
Manuel Burgos Payán,
Jesús Riquelme Santos and
Ángel Gaspar González Rodríguez
Renewable Energy, 2015, vol. 80, issue C, 219-229
Abstract:
The classical operation strategy of wind farms seeks each wind turbine to convert as much aerodynamic power as available from the incoming airflow. But this does not warranty that the power converted by the whole wind farm be a maximum due to the interaction between turbines (wake effect). Unlike the conventional operation, this paper proposes the individual selection of the operation point of each turbine so that the overall production of the wind farm is maximized. To reach that goal, the power produced by some upwind turbines is slightly reduced in order to increase the available aerodynamic power for the downwind turbines, which results in an increase of the overall wind farm energy extraction. The optimization is performed by means of a genetic algorithm that selects the optimal pitch angle and tip speed ratio of each individual wind turbine, in order to maximize the overall wind farm production.
Keywords: Genetic algorithm; Offshore wind farm; Wake effect; Wind energy; Wind farm; Wind farm operation (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148115000993
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:80:y:2015:i:c:p:219-229
DOI: 10.1016/j.renene.2015.02.009
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().