LAPSE:2023.35866
Published Article
LAPSE:2023.35866
Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model
Zhiwen Deng, Chang Xu, Zhihong Huo, Xingxing Han, Feifei Xue
May 24, 2023
In recent years, a major focus on wind farm wake control is to maximise the production of wind farms. To improve the power generation efficiency of wind farms through wake regulation, this study investigates yaw optimisation for wind farm production maximisation from the perspective of time-varying wakes. To this end, we first deduce a simplified dynamic wake model according to the momentum conservation theory and backward difference method. The accuracy of the proposed model is verified by simulation comparisons. Then, the time lag of wake propagation and its impact on wind farm production maximisation through wake meandering is analysed. On this basis, a yaw optimisation method for increasing wind farm energy capture is presented. This optimisation method uses the proposed dynamic wake model for wind farm prediction. The results indicate that the optimisation period is critical to the effect of the optimisation method on wind farm energy capture.
Keywords
dynamic wake model, production maximisation, wind farm, yaw meandering
Suggested Citation
Deng Z, Xu C, Huo Z, Han X, Xue F. Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model. (2023). LAPSE:2023.35866
Author Affiliations
Deng Z: College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China [ORCID]
Xu C: College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China; College of Energy and Electric Engineering, Hohai University, Nanjing 211100, China
Huo Z: College of Energy and Electric Engineering, Hohai University, Nanjing 211100, China
Han X: College of Energy and Electric Engineering, Hohai University, Nanjing 211100, China
Xue F: College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China [ORCID]
Journal Name
Energies
Volume
16
Issue
9
First Page
3932
Year
2023
Publication Date
2023-05-06
Published Version
ISSN
1996-1073
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Original Submission
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PII: en16093932, Publication Type: Journal Article
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LAPSE:2023.35866
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doi:10.3390/en16093932
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May 24, 2023
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May 24, 2023
 
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Calvin Tsay
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