Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions

Bingzheng Dou; Michele Guala; Liping Lei; Pan Zeng

doi:10.1016/j.apenergy.2019.03.164

Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions

Bingzheng Dou, Michele Guala, Liping Lei, Pan Zeng

Civil, Environmental, and Geo- Engineering

Research output: Contribution to journal › Article › peer-review

60 Scopus citations

Abstract

Predicting the spatial evolution of horizontal-axis turbine wakes is a key factor to enhance the performance of wind and hydrokinetic power plants. The yaw angle misalignment is not only important to account for the uncertainty of the wind direction, but also a control strategy to improve the energy production averaged over the turbine array. In this paper, a new wake model, based on the skew-normal distribution and conservation of mass and momentum, is proposed to predict the turbine wake velocity distribution for given yaw angles. The new model is experimentally validated through wake measurements of yawed miniature wind and hydrokinetic turbines, in wind tunnel and open channel flows, respectively. Predictive capabilities extend from the spatial distribution of the maximum velocity deficit at hub height, to the spanwise asymmetry of the velocity distribution about the wake center.

Original language	English (US)
Pages (from-to)	1383-1395
Number of pages	13
Journal	Applied Energy
Volume	242
DOIs	https://doi.org/10.1016/j.apenergy.2019.03.164
State	Published - May 15 2019

Bibliographical note

Funding Information:
The work was supported by National Natural Science Foundation of China (No. 51575296 and No. 51875305 ). The support provided by China Scholarship Council ( 201706210200 ) during a visit of Bingzheng Dou to University of Minnesota is acknowledged. Besides, Jing Lu, Qiuyan Zhang from Northeast Normal University and Lina Ji from Beijing Normal University also gave some valuable suggestions about the velocity distribution during their visits to University of Minnesota . The authors are grateful to Giulia Ravanelli from Universita' di Trento and Mirko Musa at University of Minnesota for providing the hydrokinetic turbine dataset.

Funding Information:
The work was supported by National Natural Science Foundation of China (No. 51575296 and No. 51875305). The support provided by China Scholarship Council (201706210200) during a visit of Bingzheng Dou to University of Minnesota is acknowledged. Besides, Jing Lu, Qiuyan Zhang from Northeast Normal University and Lina Ji from Beijing Normal University also gave some valuable suggestions about the velocity distribution during their visits to University of Minnesota. The authors are grateful to Giulia Ravanelli from Universita’ di Trento and Mirko Musa at University of Minnesota for providing the hydrokinetic turbine dataset.

Publisher Copyright:
© 2019 Elsevier Ltd

Keywords

Hydrokinetic
Renewable energy
Rivers
Wake model
Wind turbine
Yaw

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.apenergy.2019.03.164

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title = "Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions",

abstract = "Predicting the spatial evolution of horizontal-axis turbine wakes is a key factor to enhance the performance of wind and hydrokinetic power plants. The yaw angle misalignment is not only important to account for the uncertainty of the wind direction, but also a control strategy to improve the energy production averaged over the turbine array. In this paper, a new wake model, based on the skew-normal distribution and conservation of mass and momentum, is proposed to predict the turbine wake velocity distribution for given yaw angles. The new model is experimentally validated through wake measurements of yawed miniature wind and hydrokinetic turbines, in wind tunnel and open channel flows, respectively. Predictive capabilities extend from the spatial distribution of the maximum velocity deficit at hub height, to the spanwise asymmetry of the velocity distribution about the wake center.",

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Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions

Abstract

Bibliographical note

Keywords

UN SDGs

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