一种适用于风电场多变量输入的风能间接预测方法

Wind energy indirect prediction method suitable for multivariable input of wind power plant

Abstract

The invention discloses a wind energy indirect prediction method suitable for multivariable input of a wind power plant. The method comprises the steps of 1) predicting a wind speed; 2) predicting an average trend component by adopting a polynomial fitting method and forecasting a random component by adopting a frequency reduction prediction method; 3) integrating forecasting results of two independent components, namely, the average trend component and the random component to obtain a wind speed prediction value; and 4) making a historical wind energy and wind speed data distribution graph, performing polynomial fitting, generating a power curve, and calculating a wind energy prediction value according to the wind speed prediction value by utilizing the power curve so as to realize wind energy indirect prediction. The wind power plant with relatively high wind energy fluctuation also can be accurately predicted without depending on the influence on wind power plant modeling. In addition, the prediction method is a data-driven and adaptive method, and a prediction result of the prediction method does not depend on priori knowledge of a user.
本发明公开了一种适用于风电场多变量输入的风能间接预测方法,包括步骤:1)对风速进行预测;2)采用多项式拟合方法对平均趋势分量进行预测和采用降频预测法对随机分量进行预报;3)综合两个独立分量即平均趋势分量与随机分量的预报结果,即可得到风速的预测值;4)做出历史的风能风速数据的分布图,并利用多项式进行拟合,生成功率曲线,利用该功率曲线,根据风速预测值计算出风能预测值,从而实现风能的间接预测。本发明预测风电场发电功率物理意义明确,预测结果稳定,预测精度高。对风能波动较大的风电场也能实现精确的预测,而不依赖于对风电场建模的影响。此外,本发明预测方法是数据驱动、自适应的方法,其预测结果不依赖于使用者的先验知识。

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