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Conference object . 2016 . Peer-reviewed
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https://doi.org/10.1109/ecc.20...
Article . 2015 . Peer-reviewed
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Model-free control for wind farms using a gradient estimation-based algorithm

Authors: Julian Barreiro-Gomez; Carlos Ocampo-Martinez; Fernando Daniel Bianchi; Nicanor Quijano;

Model-free control for wind farms using a gradient estimation-based algorithm

Abstract

Wind turbines working close to other turbines experience interactions that affect the power production. These interactions arise as a consequence of wakes caused by upstream wind turbines. In order to achieve a more effective and precise control of the power generated by wind farms, the control strategy must consider these interactions. However, the phenomena involved in wake effects are complex especially in cases of large number of turbines. This paper presents the implementation of a gradient estimation-based algorithm as a model-free control for two different control schemes aimed to maximize the energy capture of a wind farm. One control is centralized, leaving to a supervisor the task of command computation and the other topology is decentralized, distributing the performing generation among wind turbines. This latter scheme aims to increase the reliability of the wind farm operation by reducing the communications needed to fulfill the objective of maximizing energy capture. Both control schemes are evaluated by simulation in the case of three-turbine wind farm.

Peer Reviewed

Country
Spain
Keywords

Turbines eòliques, :Informàtica::Automàtica i control [Àrees temàtiques de la UPC], Àrees temàtiques de la UPC::Informàtica::Automàtica i control, population dynamics, power generation control. model-free control, gradient estimation, Wind turbines--Automatic control, evolutionary game theory

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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9
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