2024
DOI: 10.1049/rpg2.13073
|View full text |Cite
|
Sign up to set email alerts
|

A novel prediction method for low wind output processes under very few samples based on improved W‐DCGAN

Shihua Liu,
Han Wang,
Weiye Song
et al.

Abstract: The threat of long‐term low wind output processes (LWOP) on the supply ability of the power system is escalating with the increasing integration of wind power. Accurate prediction of LWOP is crucial for maintaining the stable operation of the power system. However, the occurrence probability of LWOP is low and the available samples are lacking, limiting the high‐accuracy predictive modeling of LWOP. Therefore, a novel prediction method for LWOP under very few samples based on improved Wasserstein deep convolut… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 18 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?