The optimal wind speed product selection for wind energy assessment under multi-factor constraints
Wind energy is an important part of sustainable energy. Potential assessment of wind energy, based on an appropriate wind speed dataset, is crucial for wind energy development. The assessment of wind energy potential is constrained by factors such as temporal scales, land cover types, and wind grade...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | Cleaner Engineering and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666790825000060 |
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| Summary: | Wind energy is an important part of sustainable energy. Potential assessment of wind energy, based on an appropriate wind speed dataset, is crucial for wind energy development. The assessment of wind energy potential is constrained by factors such as temporal scales, land cover types, and wind grades. It is essential to identify the optimal wind speed product under these constraints for accurately characterizing wind speed and its volatility. However, existing studies often lack a comprehensive evaluation of wind speed products considering these limitations, and wind speed volatility is rarely considered in the optimal wind speed product selection. To address these issues, this paper aims to select the optimal wind speed product under multi-factor constraints, including temporal scales, land cover types, and wind grades, for wind resource assessment from CFSR, CN05.1, ERA5-Land, GLDAS, JRA55, and MERRA2. Major findings are summarized as follows: (1) CN05.1 is the most suitable product for characterizing wind speed across mainland China under multi-factor constraints, followed by ERA5-land. (2) The wind speed volatility of all six datasets is underestimated compared to actual observations. Among them, JRA55 demonstrates the best capability to depict wind speed volatility in China, followed by MERRA2 and ERA5-land. (3) ERA5-land is the optimal product for wind energy resource assessments across mainland China, offering relatively accurate characterizations of both wind speed and wind speed volatility. |
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| ISSN: | 2666-7908 |