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Wind resource in China is abundant due to its vast land mass and long coastline. Based on wind speed and direction records from wind measurement towers at six onshore sites with different geographical climate conditions in China, statistical assessment of wind characteristics and wind energy potential at height of 70 m corresponding to the hub heights of multi-megawatt wind turbines is presented and discussed in this paper. First of all, the Weibull distribution function is verified to be a reliable model for wind speed prediction and the moment method is proved to be an accurate approach for estimation of the Weibull parameters at all the sites. Moreover, the variations of mean wind speed, the Weibull parameters and wind power density at the six sites are investigated in terms of seasonal, monthly and diurnal time scales. Finally, annual energy outputs at the six sites are determined by taking a commercial wind turbine as an example to evaluate the economic feasibility of wind energy development. The results of this study indicate that the six sites in North China, Northeast China, Central China, coastal regions in East China and Southeast China are in rich wind energy areas which are suitable for wind energy utilization. In particular, among the six sites, Tongliao in North China is the most promising location for wind energy development with the maximum annual energy output of 10.33 GWh. The objective of this study is to provide useful information for wind energy development and an effective approach for wind energy potential assessment. [ABSTRACT FROM AUTHOR]

The goal of carbon neutrality provides a new opportunity for the development of renewable energy, especially for wind power. In this paper, 11 regional climate models (RCMs) including CORDEX-EA and PRECIS at two different resolutions are used to evaluate the performance in simulating the spatio-temporal characteristics for wind speed and energy potential from 1981 to 2005. The results show that most models can reproduce the spatio-temporal patterns, and the simulation of the eastern region is better than that of the western region. Besides, most of the higher-resolution models had better simulation performance for spatial-temporal patterns and inter-annual variation. Then, the weighted multi-model ensemble is used to project the changes of the wind speed and the wind power density over China's mainland during the mid-21st century under the RCP8.5 scenario. In future, a decrease in wind speed is projected by most RCMs over China, although some regions, such as the southern parts of China, are projected to have more wind energy potential. The percentage variation of annual mean wind speed will remain in the range of ±4%. The wind power density will decrease in the north and the largest decrease will be found in the northwest. However, the annual mean wind power density in the southeast China will have an increase of 2.21% in the middle of this century. The inter-annual variation of the wind power density in most regions will increase by more than 20%. However, intra-annual variation in the wind power density is likely to decrease in most regions of China, ranging from about −20% to −50%. • A weighted multi-model ensemble was used to project the changes of wind power density over China. • The changes of annual mean wind power density vary in different sub-regions of China, ranging from −3.21% to 2.21%. • The inter-annual variation of the WPD in most regions will increase by more than 20%. [ABSTRACT FROM AUTHOR]

Good knowledge of future wind energy resources is crucial for sitting and planning studies of wind farms. The simulation results from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a proposed new downscaling method based on the bidirectional gated recurrent unit (BiGRU) are both used in this paper to study future offshore wind energy resources in China. The proposed new downscaling method is validated and compared to two traditional methods. It is found that the spatial patterns of downscaled wind speed are highly consistent with the reference data, and biases are significantly reduced by the new method, especially in coastal and shallow water areas. Using the new method, we downscale the CMIP6 future projected simulation results and generate a new dataset of offshore wind speeds in China for the period of 2021–2100 with a resolution of 0.25°. Multi-model ensemble (MME) results project small decreases in the offshore wind speed and wind power density over the East China Sea and increases in those parameters over the South China Sea, for the middle and end of the 21st Century (2041–2060 and 2081–2100) under two representative scenarios (SSP2-4.5 and SSP5-8.5). • The first work on projection of future offshore wind energy resources in China. • A new downscaling method based on deep learning network was developed. • Global climate models' simulations were downscaled to high-resolution grids of 0.25°. • Small changes in future offshore wind speed and power density were projected in China. [ABSTRACT FROM AUTHOR]