Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method
To enhance the prediction accuracy of offshore wind speed, this study employs an interpolation algorithm to improve spatial resolution based on the ERA5 reanalysis dataset. The objective is to identify the optimal interpolation method and apply it to wind energy assessments in the South China Sea. T...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/1/213 |
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| author | Wenchuan Meng Zaimin Yang Zhi Rao Shuang Li Xin Lin Jingkang Peng Yuwei Cao Yingquan Chen |
| author_facet | Wenchuan Meng Zaimin Yang Zhi Rao Shuang Li Xin Lin Jingkang Peng Yuwei Cao Yingquan Chen |
| author_sort | Wenchuan Meng |
| collection | DOAJ |
| description | To enhance the prediction accuracy of offshore wind speed, this study employs an interpolation algorithm to improve spatial resolution based on the ERA5 reanalysis dataset. The objective is to identify the optimal interpolation method and apply it to wind energy assessments in the South China Sea. This paper compares the interpolation effects and accuracy of Linear, Cubic, and Bicubic interpolation methods on wind speed data, with the optimal method subsequently applied to evaluate wind resources in the South China Sea for 2023. The findings indicate that, while different interpolation methods minimally affect the correlation of wind speed data, there are notable differences in their impact on overall accuracy. The Cubic interpolation method proved to be the most effective, tripling spatial resolution and reducing wind speed errors in ERA5 data by 26%. Using this method, wind resource assessments were conducted in selected areas of the South China Sea. Results reveal that the annual available operational hours for wind turbines in most parts of the region range from 2000 to 4000 h, with fluctuations in turbine output power increasing alongside available operational hours. |
| format | Article |
| id | doaj-art-751ec77e7aba4bcc9d417642bfe493c0 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-751ec77e7aba4bcc9d417642bfe493c02025-01-10T13:17:25ZengMDPI AGEnergies1996-10732025-01-0118121310.3390/en18010213Refined Assessment Method of Offshore Wind Resources Based on Interpolation MethodWenchuan Meng0Zaimin Yang1Zhi Rao2Shuang Li3Xin Lin4Jingkang Peng5Yuwei Cao6Yingquan Chen7Energy Development Research Institute, China Southern Power Grid, Guangzhou 510530, ChinaEnergy Development Research Institute, China Southern Power Grid, Guangzhou 510530, ChinaEnergy Development Research Institute, China Southern Power Grid, Guangzhou 510530, ChinaEnergy Development Research Institute, China Southern Power Grid, Guangzhou 510530, ChinaPower Grid Planning Research Center, Guangxi Power Grid, Nanning 530023, ChinaSchool of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaTo enhance the prediction accuracy of offshore wind speed, this study employs an interpolation algorithm to improve spatial resolution based on the ERA5 reanalysis dataset. The objective is to identify the optimal interpolation method and apply it to wind energy assessments in the South China Sea. This paper compares the interpolation effects and accuracy of Linear, Cubic, and Bicubic interpolation methods on wind speed data, with the optimal method subsequently applied to evaluate wind resources in the South China Sea for 2023. The findings indicate that, while different interpolation methods minimally affect the correlation of wind speed data, there are notable differences in their impact on overall accuracy. The Cubic interpolation method proved to be the most effective, tripling spatial resolution and reducing wind speed errors in ERA5 data by 26%. Using this method, wind resource assessments were conducted in selected areas of the South China Sea. Results reveal that the annual available operational hours for wind turbines in most parts of the region range from 2000 to 4000 h, with fluctuations in turbine output power increasing alongside available operational hours.https://www.mdpi.com/1996-1073/18/1/213offshore wind powerinterpolationERA5wind resource assessment |
| spellingShingle | Wenchuan Meng Zaimin Yang Zhi Rao Shuang Li Xin Lin Jingkang Peng Yuwei Cao Yingquan Chen Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method Energies offshore wind power interpolation ERA5 wind resource assessment |
| title | Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method |
| title_full | Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method |
| title_fullStr | Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method |
| title_full_unstemmed | Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method |
| title_short | Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method |
| title_sort | refined assessment method of offshore wind resources based on interpolation method |
| topic | offshore wind power interpolation ERA5 wind resource assessment |
| url | https://www.mdpi.com/1996-1073/18/1/213 |
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