Parameter Estimation of a Gaussian Mixture Model for Wind Power Forecast Error by Riemann L-BFGS Optimization

Parameter Estimation of a Gaussian Mixture Model for Wind Power Forecast Error by Riemann L-BFGS Optimization

With the increasing penetration of wind power into the electricity grid, wind power forecast error analysis plays an important role in operations scheduling. To better describe the characteristics of power forecast error, a probability density function should be established. Compared with the Kernel...

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Bibliographic Details
Main Authors: Fuchao Ge, Yuntao Ju, Zhinan Qi, Yi Lin
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Wind power forecast error
probability density function
Gaussian mixture model
Kernel density estimation
Riemannian manifold optimization
L-BFGS
Online Access:https://ieeexplore.ieee.org/document/8404026/

Internet

https://ieeexplore.ieee.org/document/8404026/

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