A model-based climatology analysis of wind power resources at 100-m height over the Bohai Sea and the Yellow Sea
AbstractChina has set ambitious goals for the development of offshore wind energy to meet the increasing energy demand of coastal provinces. Many studies have assessed the potential offshore wind energy in Chinese territorial waters. However, few studies have focused on the climatology, variability, and extreme climate of wind speeds and wind power, especially at hub height in this area. This type of study is important for selecting promising sites for offshore wind farms. In the present study, a 35-year (1979–2013) high-resolution (7 km) wind hindcast over the Bohai Sea and the Yellow Sea (BYS) at 100-m height was constructed using the regional climate model COSMO-CLM (CCLM) driven by the ERA-Interim reanalysis dataset. The quality of wind speeds reconstructed by CCLM was assessed by a comparison with observation data at several stations. After verification, the climatology, variability, and extreme climate of winds over the BYS were spatially and temporally investigated. The results show that the 35-year mean wind speed is mostly between 7.0 and 7.5 m/s; in the coastal areas of the BYS, the mean is less than 7.0 m/s, and in the remote offshore areas, the mean is greater than 7.5 m/s. The daily mean wind speed is stronger (weaker) in winter (summer) half year, with stronger (weaker) spatial variability. Wind power density is mainly 300–500 W/m2. The interannual variability of annual mean wind speed and the wind power are in the range of 0.1–0.3 m/s and 10–40 W/m2, respectively. Decadal variances of the mean wind speed and the wind power are roughly within ±2% and ±5%, respectively, with a stronger variability along the southwestern coasts of the Yellow Sea. The distribution patterns of extreme winds (i.e., 5, 10, 30, and 50-year return values) are generally similar, with strength increasing from the northwest to the southeast. The wind energy characteristics for water areas and potential wind farm sites are summarized.