Wind Speed Forecasting via ensemble Kalman Filter

摘要：

Wind speed prediction is crucial for electricity system security and planning. In this paper, ensemble Kalman Filter (EnKF) method is employed to predict 10 minutes averaged wind speed. We use Auto-Regressive and Moving Average (ARMA) model as the state function of EnKF, pertnrb initial wind data to generate ensembles and forecast wind speed data via EnKF. The comparison with in-situ measurements shows that EnKF may be suitable for wind speed prediction and improve grid integration of wind energy.

关键词： wind speed forecasting EnKF time series model ARMA

作者: Zhang Wei Wang Weimin

作者单位: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen, China, 518055

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 73-77

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）