Skip to content

Code for multi-area adequacy assessment case study in // "Generating Multivariate Load States// Using a Conditional Variational Autoencoder"

License

Notifications You must be signed in to change notification settings

IEPG/PSCC2022-CVAE-case

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

System adequacy case study for CVAE load generation, PSCC 2022

This code accompanies the multi-area system adequancy case study of the paper Generating Multivariate Load States Using a Conditional Variational Autoencoder by Chenguang Wang, Ensieh Sharifnia, Zhi Gao, Simon H. Tindemans, Peter Palensky, accepted for publication at PSCC 2022 and a special issue of EPSR.

A preprint is available at: https://arxiv.org/abs/2110.11435. If you use (parts of) this code, please cite the preprint or published paper.

Dependencies

One non-standard Python packages are required to run the code: quadprog. List of all dependencies are avialable in the requirement.txt and mc-pscc2022.yml

Quick start

Please extract the compressed files in data\process-data\generated-load and run Multi-Area-Case-Study_PSCC2022.ipynb to reproduce case study's result

NOTE

Find Generative models at: https://github.com/ChenguangWang-Sam/PSCC2022-CVAE

About

Code for multi-area adequacy assessment case study in // "Generating Multivariate Load States// Using a Conditional Variational Autoencoder"

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 89.3%
  • Python 10.7%