Short-term Wind Speed Prediction Based on Wavelet Packet Decomposition and BP Neural Network

In this paper, a short-term wind speed prediction method based on BP neural network and wavelet packet decomposition was proposed to solve the problem of insufficient accuracy of wind speed prediction introduced by unstable wind speed signals. The unstable wind speed signal is transformed into a rel...

Full description

Saved in:
Bibliographic Details
Main Authors: WANG Ning, LUO Rubin, LIAO Jun, LI Jun, JIANG Yi, YANG Zechuan, YUAN Junjie
Format: Article
Language:zho
Published: Editorial Office of Control and Information Technology 2019-01-01
Series:Kongzhi Yu Xinxi Jishu
Subjects:
Online Access:http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2019.04.300
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, a short-term wind speed prediction method based on BP neural network and wavelet packet decomposition was proposed to solve the problem of insufficient accuracy of wind speed prediction introduced by unstable wind speed signals. The unstable wind speed signal is transformed into a relatively stable wind speed signal by wavelet packet decomposition, and the combination with BP neural network successfully improves the accuracy of short-term wind speed prediction. The simulation results show that the average absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) of the short-term wind speed prediction model based on wavelet packet decomposition are lower than those of other short-term wind speed prediction methods. So, it has certain advantages in short-term wind speed prediction.
ISSN:2096-5427