基于多模式融合模型的高精度风速预报方法研究

Research on High Precision Wind Speed Forecast Method Based on Multi-Mode Fusion Model

针对新能源功率预测中提升风速预报精度的需求,文章基于气象数值预报模式,利用4个背景场资料和8种参数化方案开展敏感性试验。然后,基于风速观测数据评估了集合预报成员在不同层高的风速预报效果。文章结合贝叶斯模型平均方法和相关系数滑动平均法建立了多模式融合模型,得到更加准确的确定性风速预报结果。研究显示,通过集合成员加入EC背景场进行融合后,可有效提高预报风速的相关系数,从而为提升新能源功率预测精度提供有力支撑。

In order to improve the accuracy of wind speed forecast in new energy power forecasting,based on the meteorological numerical forecast model,sensitivity tests were carried out using four background field data and eight parameterization schemes.Then,based on the wind speed observation data,the wind speed forecast effect of the set forecasting members at different layers height is evaluated.Based on the results,this paper establishes a multi-mode fusion model through Bayesian model averaging method and the correlation coefficient sliding average method,and obtains more accurate deterministic wind speed forecast results.The results show that the correlation coefficient of predicted wind speed can be improved by the ensemble members which join the EC background field for fusion,thereby providing a strong support for improving the forecast accuracy of the new energy power.