The Demo of DKEPool Applied in Transient Stability Assessment of Power System
This is the code for our paper "Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System, IJCNN2022". It is based on the code from SOPool. Many thanks!
Created by Kaixuan Chen ([email protected], [email protected])
If you find our code useful for your research, please kindly cite our paper.
@article{chen2022distribution,
title={Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System},
author={Chen, Kaixuan and Liu, Shunyu and Yu, Na and Yan, Rong and Zhang, Quan and Song, Jie and Feng, Zunlei and Song, Mingli},
journal={International Joint Conference on Neural Networks (IJCNN)},
year={2022}
}
@article{chen2022DKEPool,
title={Distribution Knowledge Embedding for Graph Pooling},
author={Chen, Kaixuan and Song, Jie and Liu, Shunyu and Yu, Na and Feng, Zunlei and Han, Gengshi and Song, Mingli},
journal={IEEE Transactions on Knowledge and Data Engineering},
year={2022}
}
Python 3.6
PyTorch > 1.0.0, tqdm, networkx, numpy
We provide scripts to run the experiments.
For DKEPool module tested on IEEE 39-BUS dataset, run
sh sh_case39.sh