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A statistical method to construct wind speed at turbine height for study of wind power in China
by
Huang, B
, Li X
, Qin, J
, Tang, W
, Li, H D
, Zhou, X
, Pan, X
in
Climate science
/ Computer simulation
/ Correlation coefficient
/ Correlation coefficients
/ Datasets
/ Energy research
/ Errors
/ Height
/ Policy and planning
/ Radiosondes
/ Statistical methods
/ Statistics
/ Turbine engines
/ Turbines
/ Weather stations
/ Wind measurement
/ Wind power
/ Wind profiles
/ Wind speed
/ Wind turbines
2020
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A statistical method to construct wind speed at turbine height for study of wind power in China
by
Huang, B
, Li X
, Qin, J
, Tang, W
, Li, H D
, Zhou, X
, Pan, X
in
Climate science
/ Computer simulation
/ Correlation coefficient
/ Correlation coefficients
/ Datasets
/ Energy research
/ Errors
/ Height
/ Policy and planning
/ Radiosondes
/ Statistical methods
/ Statistics
/ Turbine engines
/ Turbines
/ Weather stations
/ Wind measurement
/ Wind power
/ Wind profiles
/ Wind speed
/ Wind turbines
2020
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Do you wish to request the book?
A statistical method to construct wind speed at turbine height for study of wind power in China
by
Huang, B
, Li X
, Qin, J
, Tang, W
, Li, H D
, Zhou, X
, Pan, X
in
Climate science
/ Computer simulation
/ Correlation coefficient
/ Correlation coefficients
/ Datasets
/ Energy research
/ Errors
/ Height
/ Policy and planning
/ Radiosondes
/ Statistical methods
/ Statistics
/ Turbine engines
/ Turbines
/ Weather stations
/ Wind measurement
/ Wind power
/ Wind profiles
/ Wind speed
/ Wind turbines
2020
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A statistical method to construct wind speed at turbine height for study of wind power in China
Journal Article
A statistical method to construct wind speed at turbine height for study of wind power in China
Li X,
2020
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Overview
The accurate estimation of wind power is crucial not only to conduct wind energy research but also to improve policy and planning decisions for the national government. However, reliable wind speed datasets at turbine height that can be used for wind power estimation in China are very limited. In this study, the simulated wind profile (expressed by a power-law approach) is optimized using radiosonde wind speed measurements. The wind speed at a typical turbine height (80 m) is then constructed using the optimized wind profile and 10-m wind speed measured at each conventional meteorological station throughout the country. Compared with measurements, the constructed wind speed has reasonable errors (0.08 m s−1 in mean bias, 0.89 m s−1 in root mean square error, and 0.90 in correlation coefficient), which are much smaller than the model errors. Further comparison shows the constructing method in the current study outperforms the other similar statistical methods. Therefore, this method and the constructed wind speed dataset are suggested for wind energy research in China.
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