Skip to content

The code of paper 'Generative Wind Power Curve Modeling: A Self-training Deep Convolutional Network Based Method'

Notifications You must be signed in to change notification settings

IkeYang/DITU-net

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

41 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

DITU-net

The code of paper Generative Wind Power Curve Modeling Via Machine Vision: A Self-learning Deep Convolutional Network Based Method.

How to get started?

1 Download the pretrained model via https://drive.google.com/file/d/1XeMm9q6suX5hZb56OoaTy8tEC69LaD69/view?usp=sharing or https://pan.baidu.com/s/1ViAiVwqTKFXVIntmrKc7mQ with passsword: jz2t.
2 Upload your data to 'SCADAData' folder with the csv format. The first column of the data is wind speed, and the second column is wind power. (or you can utlize the 'sample.csv' provided by us for quick start.)
3 Run 'testObservedSCADAData/main.py'

About

The code of paper 'Generative Wind Power Curve Modeling: A Self-training Deep Convolutional Network Based Method'

Resources

Stars

Watchers

Forks

Packages

No packages published

Languages