Comparative Analysis of Offshore Wind Resources and Optimal Wind Speed Distribution Models in China and Europe

Yanan Chen, Ming Zhao (), Zhengxian Liu, Jianlong Ma and Lei Yang
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Yanan Chen: Department of Mechanics, School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
Ming Zhao: Department of Mechanics, School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
Zhengxian Liu: Department of Mechanics, School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
Jianlong Ma: School of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China
Lei Yang: DongFang Electric Wind Power Co., Ltd., Deyang 618000, China

Energies, 2025, vol. 18, issue 5, 1-51

Abstract: Offshore wind resources in China and Europe are systematically compared, focusing on wind speed characteristics and the selection of optimal wind speed probability distribution models. Using 20 years of data at 10 m and 100 m above sea level, seven unimodal wind speed probability distribution models were applied. The results point out that China’s offshore wind resources exhibit high spatial and temporal variability, influenced by monsoons and typhoons, while European seas are characterized by stable wind patterns. Among the models tested, the Weibull distribution is the most accurate one for wind speed fitting, while the Generalized Extreme Value and Gamma models perform better in regions with higher skewness and extreme wind events. This study highlights the importance of wind speed characteristics, such as skewness and kurtosis, in selecting the optimal model. These findings provide valuable guidance for the improvement of offshore wind energy assessments and the selection of appropriate models. Future research should explore advanced techniques, such as machine learning and hybrid models, to better capture complex wind patterns and enhance model accuracy.

Keywords: offshore wind resources; ERA5 reanalysis; wind speed probability distribution; wind speed characteristics; machine learning techniques (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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