Static voltage stability margin prediction considering new energy uncertainty based on graph attention networks and long short‐term memory networks
- DOI
- 10.1049/rpg2.12731
- Published
- 2023-05-06
- Container
- IET Renewable Power Generation
- Publisher
- Institution of Engineering and Technology (IET)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1049/rpg2.12731,
title = {Static voltage stability margin prediction considering new energy uncertainty based on graph attention networks and long short‐term memory networks},
author = {Tong Liu and Xueping Gu and Shaoyan Li and Yansong Bai and Tieqiang Wang and Xiaodong Yang},
year = {2023},
journal = {IET Renewable Power Generation},
doi = {10.1049/rpg2.12731},
url = {https://doi.org/10.1049/rpg2.12731}
}RIS
TY - JOUR TI - Static voltage stability margin prediction considering new energy uncertainty based on graph attention networks and long short‐term memory networks AU - Tong Liu AU - Xueping Gu AU - Shaoyan Li AU - Yansong Bai AU - Tieqiang Wang AU - Xiaodong Yang PY - 2023 JO - IET Renewable Power Generation DO - 10.1049/rpg2.12731 UR - https://doi.org/10.1049/rpg2.12731 ER -
APA
Liu, T., Gu, X., Li, S., Bai, Y., Wang, T., & Yang, X. (2023). Static voltage stability margin prediction considering new energy uncertainty based on graph attention networks and long short‐term memory networks. IET Renewable Power Generation. https://doi.org/10.1049/rpg2.12731
Source records
- crossref · retrieved 2026-09-24T23:25:31.317Z