A New Hybrid Prediction Method of Ultra-Short-Term Wind Power Forecasting Based on EEMD-PE and LSSVM Optimized by the GSA

A New Hybrid Prediction Method of Ultra-Short-Term Wind Power Forecasting Based on EEMD-PE and LSSVM Optimized by the GSA

Wind power time series data always exhibits nonlinear and non-stationary features, making it very difficult to accurately predict. In this paper, a novel hybrid wind power time series prediction model, based on ensemble empirical mode decomposition-permutation entropy (EEMD-PE), the least squares su...

Full description

Bibliographic Details
Main Authors: Peng Lu, Lin Ye, Bohao Sun, Cihang Zhang, Yongning Zhao, Tengjing Zhu
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Energies
Subjects:
wind power prediction
ensemble empirical mode decomposition-permutation entropy (EEMD-PE)
least squares support vector machine (LSSVM)
heuristic algorithm
Online Access:http://www.mdpi.com/1996-1073/11/4/697

Internet

http://www.mdpi.com/1996-1073/11/4/697

Similar Items