Abstract
The scale of offshore wind energy has been rapidly growing worldwide in recent years. Accurate assessment of the offshore wind energy potential and emission reduction benefits is essential to realize the ambitious targets for future installations. In this study, the Shandong Sea of China was selected as a case study, and the long-term offshore wind energy potential was assessed using ERA5 reanalysis data for the last 30 years, including the spatio-temporal variation and the technical potential of wind resources. An innovative approach to evaluate the technical potential of installed offshore wind farms based on deep learning, satellite images and ERA5 reanalysis data was proposed and applied to the Shandong Sea. The results show that (1) the highest offshore wind energy potential is observed in the northeast sea of Weihai; (2) the inter-annual variation of wind resources is relatively modest, with a pronounced monthly variability. The richest wind resources are found in the spring; (3) the electricity generation of wind resources is 12.66–30.53 GWh/year, equivalent to a reduction of 9.35–22.55 Kt of CO2 emissions; (4) as of 2023, there were 12 OWFs including 633 offshore wind turbines in Shandong Sea, generating 14,218 GWh/year of clean electricity and reducing 10,505 kt/year of CO2 emissions. The method proposed in this study is applicable to both small- and large-scale areas and allows for an accurate assessment of the electricity generation from installed offshore wind farms.
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