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Evaluating the spatio-temporal variation of China's offshore wind resources based on remotely sensed wind field data

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  • Jiang, Dong
  • Zhuang, Dafang
  • Huang, Yaohuan
  • Wang, Jianhua
  • Fu, Jingying

Abstract

Wind resource assessment in coastal areas is an important concern to develop offshore wind power. The high complexity of coastal environment entails the need for new tools that can describe the spatial variability of wind. In this paper, a distribution study of offshore wind power in China using QuikSCAT Level-2 satellite measurements at a 0.5-degree horizontal resolution was performed. Based on long-term information of daily average wind field, the paper gives an overview of the spatio-temporal distribution of wind resources in China's coastal regions. The results indicate that China has significant offshore wind energy development potential. The total offshore wind energy potential at 10m in China is approximately 660GW. The coastal region along Fu Jiang Province has the best wind resource compared with other parts of China's offshore regions. An integrated analysis was made by combining the offshore wind farm plans of coastal provinces with the spatio-temporal characteristics of the wind resource, and suggestions are presented accordingly. We find that the use of wind estimates from satellite data potentially leads to a more refined wind resource analysis.

Suggested Citation

  • Jiang, Dong & Zhuang, Dafang & Huang, Yaohuan & Wang, Jianhua & Fu, Jingying, 2013. "Evaluating the spatio-temporal variation of China's offshore wind resources based on remotely sensed wind field data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 142-148.
    • Handle: RePEc:eee:rensus:v:24:y:2013:i:c:p:142-148
    DOI: 10.1016/j.rser.2013.03.058
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    13. Yang, Zihao & Dong, Sheng, 2024. "A novel framework for wind energy assessment at multi-time scale based on non-stationary wind speed models: A case study in China," Renewable Energy, Elsevier, vol. 226(C).
    14. Liu, Yichao & Chen, Daoyi & Li, Sunwei & Chan, P.W., 2018. "Discerning the spatial variations in offshore wind resources along the coast of China via dynamic downscaling," Energy, Elsevier, vol. 160(C), pages 582-596.
    15. Lugovoy, Oleg & Gao, Shuo & Gao, Ji & Jiang, Kejun, 2021. "Feasibility study of China's electric power sector transition to zero emissions by 2050," Energy Economics, Elsevier, vol. 96(C).
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    17. Nezhad, M. Majidi & Neshat, M. & Heydari, A. & Razmjoo, A. & Piras, G. & Garcia, D. Astiaso, 2021. "A new methodology for offshore wind speed assessment integrating Sentinel-1, ERA-Interim and in-situ measurement," Renewable Energy, Elsevier, vol. 172(C), pages 1301-1313.
    18. Arun Kumar, Surisetty V.V. & Nagababu, Garlapati & Kumar, Raj, 2019. "Comparative study of offshore winds and wind energy production derived from multiple scatterometers and met buoys," Energy, Elsevier, vol. 185(C), pages 599-611.
    19. Chen, Xinping & Wang, Kaimin & Zhang, Zenghai & Zeng, Yindong & Zhang, Yao & O'Driscoll, Kieran, 2017. "An assessment of wind and wave climate as potential sources of renewable energy in the nearshore Shenzhen coastal zone of the South China Sea," Energy, Elsevier, vol. 134(C), pages 789-801.
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    22. deCastro, M. & Salvador, S. & Gómez-Gesteira, M. & Costoya, X. & Carvalho, D. & Sanz-Larruga, F.J. & Gimeno, L., 2019. "Europe, China and the United States: Three different approaches to the development of offshore wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 55-70.

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