基于模糊信息粒化的风电场短期风速预测

Short-Term Wind Speed Prediction in Wind Farm Based on Theory of Fuzzy Information Granulation

摘要: 风速的观测值往往存在大量冗余信息，导致计算量庞大并影响预测的有效性。本文提出一种基于模糊信息粒化的风电场短期风速预测方法，将原始风速观测时序数据进行模糊粒化处理，粒化后的数据既能反映风速变化特征，又能大量减少冗余，在此基础上运用支持向量机进行短期风速预测。利用武隆风电场提供的风速数据进行试验表明，该方法能够有效预测未来短期风速变化空间。

Abstract: There is often a lot of redundant information in observed values of wind speed to result in large computation and affect the predictive validity. A short-term wind speed prediction method based on theory of fuzzy information granulation is proposed to granulate wind speed data of time series. Granulated data can not only reflect the characteristics of wind but also reduce redundant information. Support vector machine can be used to forecast short-term wind speed. A group of wind speed data is provided by Wulong wind farms in Chongqing. The test result shows that this method can predict the short-term wind speed space.