广东电力2016，Vol.29Issue(4)：34-38,44,6.DOI:10.3969/j.issn.1007-290X.2016.04.006
基于改进EMD 和RBFNN的短期风速预测模型
Prediction Model for Short-term Wind Speed Based on Improved EMD and RBFNN
尹子中 1陈众 1黄健 2俞晓鹏 1邱强杰 1文亮1
作者信息
- 1. 长沙理工大学 电气与信息工程学院，湖南 长沙 410114
- 2. 邵阳市电力经济技术研究所，湖南 邵阳 422000
- 折叠
摘要
Abstract
In order to improve precision of prediction on short-term wind speed,a prediction model for short-term wind speed combining improved empirical model decomposition (EMD)and radial basis function neural network (RBFNN)is pro-posed.Firstly,extreme point symmetric extension is used for processing on preprocessed wind speed sequences so as to re-strain fringe effect in decomposition caused by traditional EMD,and piecewise cubic Hermite interpolation method is used to solve overshoot or undershoot of traditional EMD envelope lines.Then,improved EMD is used to decompose wind speed se-quences into different intrinsic mode function (IMF)components and respective RBFNN model is constructed for predic-tion.Finally,prediction results of various components are reconstructed and overlayed to get final predicted value of original wind speed.Experimental results indicate that the improved EMD-RBFNN prediction model is able to effectively improve precision of prediction on wind speed and has certain application value.关键词
风速预测/改进经验模态分解法/径向基函数神经网络Key words
wind speed prediction/improved empirical mode decomposition (EMD)/radial basis function neural network (RBFNN)分类
信息技术与安全科学引用本文复制引用
尹子中,陈众,黄健,俞晓鹏,邱强杰,文亮..基于改进EMD 和RBFNN的短期风速预测模型[J].广东电力,2016,29(4):34-38,44,6.
