基于自适应的动态三次指数平滑法的风电场风速预测

Self-adaptive and dynamic cubic ES method for wind speed forecasting

随着风力发电的快速发展,对风电场的风速实现较准确的预测也逐步成为风电领域研究的热点。为了提高风速的预测精度,综合考虑风速历史时间序列的影响,在传统的三次指数平滑方法的基础上,提出了一种自适应的动态三次指数平滑方法来进行风速预测。该方法利用了地毯式搜索方法,根据误差平方和最小的原则及时调整并获得最佳的平滑系数,然后进行后续的一步或多步风速预测。通过与传统的三次指数平滑法、灰色模型预测法比较,验证了自适应的动态三次指数平滑法在风电场风速预测中的准确性和高效性。

With the rapid development of wind power in recent years, to achieve more accurate predictions of wind speed on wind farm has gradually become an hot issue in research. To improve the wind speed forecasting accuracy for wind farm, a new self-adaptive and dynamic forecasting method is presented, which is based on the wind speed time series and traditional cubic exponential smoothing （ES） method. According to the principle of minimum error sum of squares, the smoothing factor is chosen with blanket search method and changed in time. Then one-step or multistep wind speed forecasting can be done with the new method. By comparing with the traditional cubic exponential smoothing method and gray model forecasting method, it can be proved that the self-adaptive and dynamic forecasting method in wind speed forecasting is accurate and efficient.