Wind Turbine Yaw Control Optimization and Its Impact on Performance

The optimization of wind energy conversion efficiency has been recently boosting the technology improvement and the scientific comprehension of wind turbines. In this context, the yawing behavior of wind turbines has become a key topic: the yaw control can actually be exploited for optimization at t...

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Main Authors: Davide Astolfi, Francesco Castellani, Francesco Natili
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Machines
Subjects:
Online Access:https://www.mdpi.com/2075-1702/7/2/41
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spelling doaj-40636b5911c244e2862ab8119e33353e2020-11-25T00:25:24ZengMDPI AGMachines2075-17022019-06-01724110.3390/machines7020041machines7020041Wind Turbine Yaw Control Optimization and Its Impact on PerformanceDavide Astolfi0Francesco Castellani1Francesco Natili2Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, ItalyDepartment of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, ItalyDepartment of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, ItalyThe optimization of wind energy conversion efficiency has been recently boosting the technology improvement and the scientific comprehension of wind turbines. In this context, the yawing behavior of wind turbines has become a key topic: the yaw control can actually be exploited for optimization at the level of single wind turbine and of wind farm (for example, through active control of wakes). On these grounds, this work is devoted to the study of the yaw control optimization on a 2 MW wind turbine. The upgrade is estimated by analysing the difference between the measured post-upgrade power and a data driven model of the power according to the pre-upgrade behavior. Particular attention has therefore been devoted to the formulation of a reliable model for the pre-upgrade power of the wind turbine of interest, as a function of the operation variables of all the nearby wind turbines in the wind farm: the high correlation between the possible covariates of the model indicates that Principal Component Regression (PCR) is an adequate choice. Using this method, the obtained result for the selected test case is that the yaw control optimization provides a 1% of annual energy production improvement. This result indicates that wind turbine control optimization can non-negligibly improve the efficiency of wind turbine technology.https://www.mdpi.com/2075-1702/7/2/41wind energywind turbinescontrol and optimization
collection DOAJ
language English
format Article
sources DOAJ
author Davide Astolfi
Francesco Castellani
Francesco Natili
spellingShingle Davide Astolfi
Francesco Castellani
Francesco Natili
Wind Turbine Yaw Control Optimization and Its Impact on Performance
Machines
wind energy
wind turbines
control and optimization
author_facet Davide Astolfi
Francesco Castellani
Francesco Natili
author_sort Davide Astolfi
title Wind Turbine Yaw Control Optimization and Its Impact on Performance
title_short Wind Turbine Yaw Control Optimization and Its Impact on Performance
title_full Wind Turbine Yaw Control Optimization and Its Impact on Performance
title_fullStr Wind Turbine Yaw Control Optimization and Its Impact on Performance
title_full_unstemmed Wind Turbine Yaw Control Optimization and Its Impact on Performance
title_sort wind turbine yaw control optimization and its impact on performance
publisher MDPI AG
series Machines
issn 2075-1702
publishDate 2019-06-01
description The optimization of wind energy conversion efficiency has been recently boosting the technology improvement and the scientific comprehension of wind turbines. In this context, the yawing behavior of wind turbines has become a key topic: the yaw control can actually be exploited for optimization at the level of single wind turbine and of wind farm (for example, through active control of wakes). On these grounds, this work is devoted to the study of the yaw control optimization on a 2 MW wind turbine. The upgrade is estimated by analysing the difference between the measured post-upgrade power and a data driven model of the power according to the pre-upgrade behavior. Particular attention has therefore been devoted to the formulation of a reliable model for the pre-upgrade power of the wind turbine of interest, as a function of the operation variables of all the nearby wind turbines in the wind farm: the high correlation between the possible covariates of the model indicates that Principal Component Regression (PCR) is an adequate choice. Using this method, the obtained result for the selected test case is that the yaw control optimization provides a 1% of annual energy production improvement. This result indicates that wind turbine control optimization can non-negligibly improve the efficiency of wind turbine technology.
topic wind energy
wind turbines
control and optimization
url https://www.mdpi.com/2075-1702/7/2/41
work_keys_str_mv AT davideastolfi windturbineyawcontroloptimizationanditsimpactonperformance
AT francescocastellani windturbineyawcontroloptimizationanditsimpactonperformance
AT francesconatili windturbineyawcontroloptimizationanditsimpactonperformance
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