Probability Density Forecasting of Wind Speed Based on Quantile Regression and Kernel Density Estimation

Probability Density Forecasting of Wind Speed Based on Quantile Regression and Kernel Density Estimation

Based on quantile regression (QR) and kernel density estimation (KDE), a framework for probability density forecasting of short-term wind speed is proposed in this study. The empirical mode decomposition (EMD) technique is implemented to reduce the noise of raw wind speed series. Both linear QR (LQR...

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Bibliographic Details
Main Authors: Lei Zhang, Lun Xie, Qinkai Han, Zhiliang Wang, Chen Huang
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Energies
Subjects:
probability density forecasting
wind speed series
quantile regression
kernel density estimation
signal decomposing algorithm
Online Access:https://www.mdpi.com/1996-1073/13/22/6125

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