A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint

Shutang You; Yinfeng Zhao; Mirka Mandich; Yi Cui; Hongyu Li; Huangqing Xiao; Summer Fabus; Yu Su; Yilu Liu; Haoyu Yuan; Huaiguang Jiang; Jin Tan; Yingchen Zhang

A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint

Shutang You, Yinfeng Zhao, Mirka Mandich, Yi Cui, Hongyu Li, Huangqing Xiao, Summer Fabus, Yu Su, Yilu Liu, Haoyu Yuan, Huaiguang Jiang, Jin Tan, Yingchen Zhang

Power Systems Engineering

University of Tennessee at Knoxville

Research output: Contribution to conference › Paper

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-signal stability. Test results verified the accuracy and effectiveness of the artificial intelligence tool for power grid stability assessment.

Original language	American English
Number of pages	9
State	Published - 2020
Event	IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm) - Duration: 11 Nov 2020 → 13 Nov 2020

Conference

Conference	IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm)
Period	11/11/20 → 13/11/20

NREL Publication Number

NREL/CP-5D00-77845

Keywords

artificial intelligence
power grid
stability assessment

Access to Document

https://www.nrel.gov/docs/fy21osti/77845.pdf

Cite this

You, S., Zhao, Y., Mandich, M., Cui, Y., Li, H., Xiao, H., Fabus, S., Su, Y., Liu, Y., Yuan, H., Jiang, H., Tan, J., & Zhang, Y. (2020). A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint. Paper presented at IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm). https://www.nrel.gov/docs/fy21osti/77845.pdf

@conference{2a81171bf2a847139456e184f56c7d0b,

title = "A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint",

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-signal stability. Test results verified the accuracy and effectiveness of the artificial intelligence tool for power grid stability assessment.",

keywords = "artificial intelligence, power grid, stability assessment",

author = "Shutang You and Yinfeng Zhao and Mirka Mandich and Yi Cui and Hongyu Li and Huangqing Xiao and Summer Fabus and Yu Su and Yilu Liu and Haoyu Yuan and Huaiguang Jiang and Jin Tan and Yingchen Zhang",

year = "2020",

language = "American English",

note = "IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm) ; Conference date: 11-11-2020 Through 13-11-2020",

}

You, S, Zhao, Y, Mandich, M, Cui, Y, Li, H, Xiao, H, Fabus, S, Su, Y, Liu, Y, Yuan, H, Jiang, H, Tan, J & Zhang, Y 2020, 'A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint', Paper presented at IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm), 11/11/20 - 13/11/20. <https://www.nrel.gov/docs/fy21osti/77845.pdf>

TY - CONF

T1 - A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint

AU - You, Shutang

AU - Zhao, Yinfeng

AU - Mandich, Mirka

AU - Cui, Yi

AU - Li, Hongyu

AU - Xiao, Huangqing

AU - Fabus, Summer

AU - Su, Yu

AU - Liu, Yilu

AU - Yuan, Haoyu

AU - Jiang, Huaiguang

AU - Tan, Jin

AU - Zhang, Yingchen

PY - 2020

Y1 - 2020

N2 - 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-signal stability. Test results verified the accuracy and effectiveness of the artificial intelligence tool for power grid stability assessment.

AB - 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-signal stability. Test results verified the accuracy and effectiveness of the artificial intelligence tool for power grid stability assessment.

KW - artificial intelligence

KW - power grid

KW - stability assessment

M3 - Paper

T2 - IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm)

Y2 - 11 November 2020 through 13 November 2020

ER -

A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint

Abstract

Conference

NREL Publication Number

Keywords

Access to Document

Fingerprint

Cite this