Wind Speed Prediction Performance Based on Modal Decomposition Method

Zhichao Hu, Runfeng Zhang, Z. Zenkova, Yue Wang
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引用次数: 2

Abstract

As wind energy and other renewable energy sources are valued by various countries, it is very important to estimate and predict the wind energy level. The accuracy of wind energy prediction mainly depends on the accuracy of wind speed prediction. Therefore, to seek ways of improvement the accuracy of wind speed prediction has become the most important issue. In this paper, three different decomposition methods and commonly used wind speed prediction methods are used to compose the corresponding combined models, and to study which combined prediction model has higher accuracy. According to data research conducted by the National Meteorological Science Center, experiments show that the prediction accuracy of the combined prediction model using the Variational mode decomposition (VMD) method is higher than that of the combined prediction model using empirical mode decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD).
基于模态分解方法的风速预测性能
由于风能和其他可再生能源受到各国的重视,对风能水平的估计和预测是非常重要的。风能预测的准确性主要取决于风速预测的准确性。因此,寻求提高风速预报精度的方法已成为当务之急。本文采用三种不同的分解方法和常用的风速预测方法组成相应的组合模型,研究哪种组合预测模型精度更高。根据国家气象科学中心的数据研究,实验表明,变分模态分解(VMD)方法组合预测模型的预测精度高于经验模态分解(EMD)和集合经验模态分解(EEMD)组合预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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