基于EMD-GRNN和概率统计结合的短期风速预测

计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 72-75.

基于EMD-GRNN和概率统计结合的短期风速预测

朱亚,孙冬梅,何响,刘曼曼

南京工业大学自动化与电气工程学院南京211816;南京工业大学自动化与电气工程学院南京211816;南京工业大学自动化与电气工程学院南京211816;南京工业大学自动化与电气工程学院南京211816

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受江苏省科技厅工业科学支撑项目(BE2009166)资助

Short-term Wind Speed Prediction Based on EMD-GRNN Combination of Probability and Statistics

ZHU Ya,SUN Dong-mei,HE Xiang and LIU Man-man

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 文中参照风电场原始数据,依据风速的特性,提出了一种基于EMD-GRNN和概率统计结合的短期风速预测算法。首先对原始数据进行预处理,然后对原始风速进行经验模态分解(EMD),获得原风速的所有基本模态分量(IMF)；接着对各分量数据进行重构得到训练样本和预测样本,利用训练样本训练GRNN网络,使网络具备预测能力；最后对各个分量输出的数据进行概率统计。仿真实验表明,与单独的神经网络预测方法相比,结合概率统计的EMD-GRNN预测模型,具有更好的预测精度和稳定性。

关键词: 短期风速预测,经验模态分解,GRNN网络,概率统计中图法分类号TP391文献标识码A

Abstract: Referring to raw data of the wind farm and based on the characteristics of wind speed,this article proposed a short-term wind speed prediction algorithm based on EMD-GRNN combination of probability and statistics．The paper firstly preprocessed the original data,then took advantage of empirical mode decomposition (E-MD) on the original wind speed,to get all the basic raw wind modal component (IMF).Nextly,this paper proceeded to reconstruct the data of each component to get the training samples and forecasting samples and utilized the train-ing sample to train GRNN network to make the network predictive capability.Finally this paper made a probability statistics on the output data of the various components．Simulation results show that the EMD-GRNN prediction model of combination of probability and statistics has good predictive accuracy and stability.

Key words: Short-term wind speed prediction,EMD,GRNN network,Probability statistics

朱亚,孙冬梅,何响,刘曼曼. 基于EMD-GRNN和概率统计结合的短期风速预测[J]. 计算机科学, 2014, 41(Z6): 72-75. https://doi.org/

ZHU Ya,SUN Dong-mei,HE Xiang and LIU Man-man. Short-term Wind Speed Prediction Based on EMD-GRNN Combination of Probability and Statistics[J]. Computer Science, 2014, 41(Z6): 72-75. https://doi.org/

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