基于秩次集对分析的风电功率实时预测研究

WIND POWER REAL-TIME PREDICTION BASED ON RANK AND SET PAIR ANALYSIS

提出基于秩次集对分析的风电功率实时预测模型,将物理意义明确、算法简单的秩次集对分析应用到风电功率时间序列实时预测中。根据选择最相似集合方法的不同,建立3个不同的模型,并利用两个风电场的实测数据进行仿真预测,结果表明等容最小间距法在实时预测中具有良好的预测性能,有一定的应用价值。

This paper presents a wind power real-timeprediction model based on rank and set pair analysis, which apply to wind power time series forecasting is simple and has clear physical meaning. This paper has established three different models based on different methods of choosing most similar collection. Taking two wind farm as example, the forecasting results showed that the equal volume minimum distance method has good prediction of the performance, so it has good practical value.