从宏观到微观：中国沿海风能潜力的多尺度评估方法

Abstract As offshore wind power advances toward deeper waters, clustered deployments, and larger turbine capacities, there is an increasing demand for comprehensive wind energy resource assessment methods to meet the growing complexities of wind energy construction. Current assessments, limited to either macro-scale or micro-scale, often overlook wake effects of dense wind farms . Additionally, micro-scale wind resource assessments based on satellite data neglect regional differences in wind shear indices, leading to inaccuracies in wind speed evaluations. Therefore, this study proposes a comprehensive wind energy resource assessment framework that integrates macro-scale, low-resolution analysis with micro-scale, high-resolution evaluation. At the macro level, in addition to classic wind energy indicators, variability indicators, and cost indicators, the existing offshore wind farm areas and their potential wake effect areas are particularly considered. Then these factors are synthesized to derive the Comprehensive Offshore Wind Energy Index (COWEI). To refine the resolution of macro-scale assessment, based on the selected high-COWEI value area, an improved micro-scale assessment is designed. Specifically, we derive wind speed data at the typical 100-m wind turbine hub height from 10-m SAR satellite wind speed data, accounting for regional wind shear variations, which more precisely evaluate wind speed in regional areas. The main findings are as follows: (1) as of June 2024, 6516 offshore wind turbines (OWTs) have been installed along China’s coastline, with an average installation depth of 14.8 m and an average distance of 32.7 km from the coast; (2) wake effect areas are approximately three times the size of the wind farm areas, with significantly larger wake areas observed in southern sea regions; (3) the Taiwan Strait is identified as the most suitable region for wind farm development; (4) integration of macro-scale with micro-scale assessment not only enhances general understanding of wind resources but also captures details in local regions. This multi-scale assessment framework demonstrates the comprehensive application of geoscience methodologies in energy research and provides a solid foundation for offshore wind farm planning and site selection.