LAPSE:2023.20297v1
Published Article

LAPSE:2023.20297v1
Study on Atmospheric Stability and Wake Attenuation Constant of Large Offshore Wind Farm in Yellow Sea
March 17, 2023
Abstract
Power generation estimation is one of the key steps in wind farm micro-sitting, and its accuracy is related to the wake decay constant in the wake model. Considering the influence of wind resource distribution in different regions, this study carried out interval optimization for the wake decay constant of offshore wind farms in the Yellow Sea region of China. Given the very small length of the sea surface roughness, atmospheric stability is a critical factor influencing the wake extent and recovery speed of offshore wind farms. WAsP 10 (Wind Atlas Analysis and Application software) simulates the wake of various scenarios, and the selection range of wake attenuation constant is investigated by combining the cases of two offshore wind farms in the Yellow Sea region. The study found that the higher the atmospheric stability, the larger the wake and the lower the wake attenuation coefficient. The Yellow Sea wind farm’s wake error system is between 0.03 and 0.04, and the forecast error can be controlled to within 3%. When simulating the wind farm at Yellow Sea offshore for improving power generation and economic evaluation, it is critical to select the correct value range of wake decay constant.
Power generation estimation is one of the key steps in wind farm micro-sitting, and its accuracy is related to the wake decay constant in the wake model. Considering the influence of wind resource distribution in different regions, this study carried out interval optimization for the wake decay constant of offshore wind farms in the Yellow Sea region of China. Given the very small length of the sea surface roughness, atmospheric stability is a critical factor influencing the wake extent and recovery speed of offshore wind farms. WAsP 10 (Wind Atlas Analysis and Application software) simulates the wake of various scenarios, and the selection range of wake attenuation constant is investigated by combining the cases of two offshore wind farms in the Yellow Sea region. The study found that the higher the atmospheric stability, the larger the wake and the lower the wake attenuation coefficient. The Yellow Sea wind farm’s wake error system is between 0.03 and 0.04, and the forecast error can be controlled to within 3%. When simulating the wind farm at Yellow Sea offshore for improving power generation and economic evaluation, it is critical to select the correct value range of wake decay constant.
Record ID
Keywords
evaluation of power generation, wake decay constant, wake flow, WAsP, wind farm in coastal waters
Subject
Suggested Citation
Liu H, Chen J, Zhang J, Chen Y, Wen Y, Zhang X, Yan Z, Li Q. Study on Atmospheric Stability and Wake Attenuation Constant of Large Offshore Wind Farm in Yellow Sea. (2023). LAPSE:2023.20297v1
Author Affiliations
Liu H: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Chen J: Department of Electrical Engineering, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100096, China
Zhang J: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China [ORCID]
Chen Y: Department of Atmospheric Science, School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China [ORCID]
Wen Y: Department of Electrical Engineering, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100096, China
Zhang X: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Yan Z: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Li Q: Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
Chen J: Department of Electrical Engineering, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100096, China
Zhang J: Beijing RETEC New Energy Technology Co., Ltd., Beijing 100079, China [ORCID]
Chen Y: Department of Atmospheric Science, School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China [ORCID]
Wen Y: Department of Electrical Engineering, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100096, China
Zhang X: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Yan Z: CSSC Windpower Development Co., Ltd., Beijing 100097, China
Li Q: Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
Journal Name
Energies
Volume
16
Issue
5
First Page
2227
Year
2023
Publication Date
2023-02-25
ISSN
1996-1073
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PII: en16052227, Publication Type: Journal Article
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LAPSE:2023.20297v1
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https://doi.org/10.3390/en16052227
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Mar 17, 2023
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