Wind Power Assessment Based on the WRF Model
- 作者：LI Ji-HangGUO Zhen-HaiWANG Hui-Jun
- 会议时间：2014-11-03
- 关键词：wind power assessment ; anemometer tower data ; WRF model ; variance analysis
- 作者单位：LI Ji-Hang(Nansen-Zhu International Research Centre (NZC),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;Institute of Tropical and Marine Meteorology,CMA Guangzhou,Guangzhou 510080,China)GUO Zhen-Hai(State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG),Institute of Atmospheric)WANG Hui-Jun(Nansen-Zhu International Research Centre (NZC),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China)
- 会议名称：第31届中国气象学会年会
- 会议地点：北京
- 主办单位：中国气象学会
- 语种：chi
摘要
Assessing wind energy is a key step in selecting a site for a wind farm.The accuracy of the assessment is essential for the future operation of the wind farm.There are two main methods for assessing wind power; one is based on observational data and the other relies on mesoscale numerical weather prediction (NWP).In this study, the wind power of the Liaoning coastal wind farm was evaluated using observations from an anemometer tower and simulations by the Weather Research and Forecasting (WRF) model, to see whether the WRF model can produce a valid assessment of the wind power and whether the downscaling process can provide a better evaluation.The paper presents long-term wind data analysis in terms of annual, seasonal, and diurnal variations at the wind farm, which is located on the east coast of Liaoning Province.The results showed that, in spring and summer, the wind speed, wind direction, wind power density, and other main indicators were consistent between the two methods.However, the values of these parameters from the WRF model were significantly higher than the observations from the anemometer tower.Therefore, the causes of the diferences between the two methods were further analyzed.There was much more deviation in the original material, National Centers for Environmental Prediction (NCEP) final (FNL) Operational Global Analysis data, in autumn and winter than in spring and summer.As the region is vulnerable to cold-air outbreaks and windy weather in autumn and winter, and the model usually forecasted stronger high or low systems with a longer duration, the predicted wind speed from the WRF model was too large.