风能资源评估精准度提升策略的研究OA

In the preliminary development of wind farms,it is essential to conduct quantitative assessments of wind resource and power generation capacity predictions,as the accuracy of these evaluations directly impacts the economy and feasibility of projects.In order to improve the accuracy of wind energy resource assessment,this paper uses quantitative analysis method to comprehensively compare the main parameter matching degree between mainstream wind energy resource data analysis platforms and actual wind measurement towers.And a comparative analysis is conducted on the fitting degree between mesoscale time series data from different data sources and actual wind tower measurement data from multiple dimensions.Finally,taking a planned wind farm site area in Lanzhou City as an example,the accuracy of virtual wind measurement towers is studied based on altitude and distance factors.The research results show that:1)The Envision's Greenwich platform has the highest matching degree with the measured data of wind measurement towers in terms of annual average wind speed,overall average wind shear index,and Weibull distribution shape parameters.It is recommended to choose this data analysis platform when wind energy resource assessment lacks measured data of wind measurement towers and requires basic data query of wind energy resources.2)When selecting mesoscale time series data as the reference dataset for representative annual analysis in the preprocessing of measured data,it is recommended to prioritize the use of DX-Wind Style Energy&Meteorology Platform data sources in mountainous areas of China,MERRA2 reanalysis data sources in plain areas,and ERA5 reanalysis data sources in coastal areas.3)For modeling wind farms,mesoscale time series data from high-low altitude dual virtual wind measurement towers are used as input conditions for wind field simulation calculations,or remote actual wind measurement tower measurement data is fused and interpolated with mesoscale time series data from the target machine location area to construct a remote mesoscale fusion virtual wind measurement tower,the mesoscale time series data from this virtual wind measurement tower is used as input conditions for wind field simulation calculations,both methods can significantly improve the accuracy and reliability of wind energy resource assessment.