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Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms

Ahmad, Tanvir; Basit, Abdul; Ahsan, Muneeb; Coupiac, Olivier; Girard, Nicolas; Kazemtabrizi, Behzad; Matthews, Peter

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Authors

Tanvir Ahmad

Abdul Basit

Muneeb Ahsan

Olivier Coupiac

Nicolas Girard



Abstract

This paper presents, with a live field experiment, the potential of increasing wind farm power generation by optimally yawing upstream wind turbine for reducing wake effects as a part of the SmartEOLE project. Two 2MW turbines from the Le Sole de Moulin Vieux (SMV) wind farm are used for this purpose. The upstream turbine (SMV6) is operated with a yaw offset (α) in a range of −12◦ to 8◦ for analysing the impact on the downstream turbine (SMV5). Simulations are performed with intelligent control strategies for estimating optimum α settings. Simulations show that optimal α can increase net production of the two turbines by more than 5%. The impact of α on SMV6 is quantified using the data obtained during the experiment. A comparison of the data obtained during theexperimentiscarriedoutwithdataobtainedduringnormaloperationsinsimilarwindconditions. This comparison show that an optimum or near-optimum α increases net production by more than 5% in wake affected wind conditions, which is in confirmation with the simulated results.

Citation

Ahmad, T., Basit, A., Ahsan, M., Coupiac, O., Girard, N., Kazemtabrizi, B., & Matthews, P. (2019). Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms. Energies, 12(7), Article 1266. https://doi.org/10.3390/en12071266

Journal Article Type Article
Acceptance Date Mar 29, 2019
Online Publication Date Apr 2, 2019
Publication Date Apr 2, 2019
Deposit Date Apr 3, 2019
Publicly Available Date Apr 4, 2019
Journal Energies
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 12
Issue 7
Article Number 1266
DOI https://doi.org/10.3390/en12071266

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).





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