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Title: A Review on Artificial Intelligence for Grid Stability Assessment

Abstract

Artificial intelligence provides a convenient route for power grid stability assessment. Compared with simulation-based approaches, artificial intelligence can potentially save time on model development and numerical computation in stability assessment. This paper first reviewed existing literature on using artificial intelligence for power grid stability assessment. Then a machine-leaning-based tool is presented and developed to assess power grid transient stability, frequency stability, and small signals stability. Test results verified the accuracy and effectiveness of the AI tool for power grid stability assessment.

Authors:
 [1];  [2];  [2];  [2];  [2];  [1];  [1];  [2];  [1];  [3];  [4];  [4];  [4]
  1. ORNL
  2. University of Tennessee, Knoxville (UTK)
  3. University of Tennessee (UT)
  4. National Renewable Energy Laboratory (NREL)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1771880
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) - Tempe, Arizona, United States of America - 11/11/2020 5:00:00 AM-1/13/2021 5:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

You, Shutang, Zhao, Yinfeng, Mandich, Mirka, CUI, YI, Li, Hongyu, Xiao, Huangqing, Fabus, Summer F., Su, Yu, Liu, Yilu, Yuan, Haoyu, Jiang, Huaiguang, Tan, Jin, and Zhang, Yingchen. A Review on Artificial Intelligence for Grid Stability Assessment. United States: N. p., 2020. Web. doi:10.1109/SmartGridComm47815.2020.9302990.
You, Shutang, Zhao, Yinfeng, Mandich, Mirka, CUI, YI, Li, Hongyu, Xiao, Huangqing, Fabus, Summer F., Su, Yu, Liu, Yilu, Yuan, Haoyu, Jiang, Huaiguang, Tan, Jin, & Zhang, Yingchen. A Review on Artificial Intelligence for Grid Stability Assessment. United States. https://doi.org/10.1109/SmartGridComm47815.2020.9302990
You, Shutang, Zhao, Yinfeng, Mandich, Mirka, CUI, YI, Li, Hongyu, Xiao, Huangqing, Fabus, Summer F., Su, Yu, Liu, Yilu, Yuan, Haoyu, Jiang, Huaiguang, Tan, Jin, and Zhang, Yingchen. 2020. "A Review on Artificial Intelligence for Grid Stability Assessment". United States. https://doi.org/10.1109/SmartGridComm47815.2020.9302990. https://www.osti.gov/servlets/purl/1771880.
@article{osti_1771880,
title = {A Review on Artificial Intelligence for Grid Stability Assessment},
author = {You, Shutang and Zhao, Yinfeng and Mandich, Mirka and CUI, YI and Li, Hongyu and Xiao, Huangqing and Fabus, Summer F. and Su, Yu and Liu, Yilu and Yuan, Haoyu and Jiang, Huaiguang and Tan, Jin and Zhang, Yingchen},
abstractNote = {Artificial intelligence provides a convenient route for power grid stability assessment. Compared with simulation-based approaches, artificial intelligence can potentially save time on model development and numerical computation in stability assessment. This paper first reviewed existing literature on using artificial intelligence for power grid stability assessment. Then a machine-leaning-based tool is presented and developed to assess power grid transient stability, frequency stability, and small signals stability. Test results verified the accuracy and effectiveness of the AI tool for power grid stability assessment.},
doi = {10.1109/SmartGridComm47815.2020.9302990},
url = {https://www.osti.gov/biblio/1771880}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Nov 01 00:00:00 EDT 2020},
month = {Sun Nov 01 00:00:00 EDT 2020}
}

Conference:
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