Adding Power of Artificial Intelligence to Situational Awareness of Large Interconnections Dominated by Inverter-Based Resources

Lin Zhu; Yinfeng Zhao; Yi Cui; Shutang You; Wenpeng Yu; Shenyuan Liu; He Yin; Chang Chen; Yuru Wu; Wei Qiu; Mirka Mandich; Hongyu Li; Adedasola Ademola; Chengwen Zhang; Chujie Zeng; Xinlan Jia; Weikang Wang; Haoyu Yuan; Huaiguang Jiang; Jin Tan; Yilu Liu

doi:10.1049/hve2.12157

Adding Power of Artificial Intelligence to Situational Awareness of Large Interconnections Dominated by Inverter-Based Resources

Lin Zhu
, Yinfeng Zhao
, Yi Cui
, Shutang You
, Wenpeng Yu
, Shenyuan Liu
, He Yin
, Chang Chen
, Yuru Wu
, Wei Qiu
, Mirka Mandich
, Hongyu Li
, Adedasola Ademola
, Chengwen Zhang
, Chujie Zeng
, Xinlan Jia
, Weikang Wang
, Haoyu Yuan
, Huaiguang Jiang
, Jin Tan

Yilu Liu

University of Tennessee, Knoxville
Oak Ridge National Laboratory

Research output: Contribution to journal › Article › peer-review

7 Scopus Citations

Abstract

Large-scale power systems exhibit more complex dynamics due to the increasing integration of inverter-based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide-Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large-scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra-high density synchrophasor and point-on-wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)-based advanced applications are introduced, including AI-based inertia estimation, AI-based disturbance size and location estimation, AI-based system stability assessment, and AI-based data authentication.

Original language	American English
Pages (from-to)	924-937
Number of pages	14
Journal	High Voltage
Volume	6
Issue number	6
DOIs	https://doi.org/10.1049/hve2.12157 https://doi.org/10.1049/hve2.12157
State	Published - 2021

Bibliographical note

Publisher Copyright:
© 2021 The Authors. High Voltage published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology and China Electric Power Research Institute.

NLR Publication Number

NREL/JA-5C00-80350

Keywords

artificial intelligence
inverter-based renewables
situational awareness
smart grid
wide-area measurement system

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Zhu, L., Zhao, Y., Cui, Y., You, S., Yu, W., Liu, S., Yin, H., Chen, C., Wu, Y., Qiu, W., Mandich, M., Li, H., Ademola, A., Zhang, C., Zeng, C., Jia, X., Wang, W., Yuan, H., Jiang, H., ... Liu, Y. (2021). Adding Power of Artificial Intelligence to Situational Awareness of Large Interconnections Dominated by Inverter-Based Resources. High Voltage, 6(6), 924-937. https://doi.org/10.1049/hve2.12157, https://doi.org/10.1049/hve2.12157

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title = "Adding Power of Artificial Intelligence to Situational Awareness of Large Interconnections Dominated by Inverter-Based Resources",

abstract = "Large-scale power systems exhibit more complex dynamics due to the increasing integration of inverter-based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide-Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large-scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra-high density synchrophasor and point-on-wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)-based advanced applications are introduced, including AI-based inertia estimation, AI-based disturbance size and location estimation, AI-based system stability assessment, and AI-based data authentication.",

keywords = "artificial intelligence, inverter-based renewables, situational awareness, smart grid, wide-area measurement system",

author = "Lin Zhu and Yinfeng Zhao and Yi Cui and Shutang You and Wenpeng Yu and Shenyuan Liu and He Yin and Chang Chen and Yuru Wu and Wei Qiu and Mirka Mandich and Hongyu Li and Adedasola Ademola and Chengwen Zhang and Chujie Zeng and Xinlan Jia and Weikang Wang and Haoyu Yuan and Huaiguang Jiang and Jin Tan and Yilu Liu",

note = "Publisher Copyright: {\textcopyright} 2021 The Authors. High Voltage published by John Wiley \& Sons Ltd on behalf of The Institution of Engineering and Technology and China Electric Power Research Institute.",

year = "2021",

doi = "10.1049/hve2.12157",

language = "American English",

volume = "6",

pages = "924--937",

journal = "High Voltage",

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Zhu, L, Zhao, Y, Cui, Y, You, S, Yu, W, Liu, S, Yin, H, Chen, C, Wu, Y, Qiu, W, Mandich, M, Li, H, Ademola, A, Zhang, C, Zeng, C, Jia, X, Wang, W, Yuan, H, Jiang, H, Tan, J & Liu, Y 2021, 'Adding Power of Artificial Intelligence to Situational Awareness of Large Interconnections Dominated by Inverter-Based Resources', High Voltage, vol. 6, no. 6, pp. 924-937. https://doi.org/10.1049/hve2.12157, https://doi.org/10.1049/hve2.12157

TY - JOUR

T1 - Adding Power of Artificial Intelligence to Situational Awareness of Large Interconnections Dominated by Inverter-Based Resources

AU - Zhu, Lin

AU - Zhao, Yinfeng

AU - Cui, Yi

AU - You, Shutang

AU - Yu, Wenpeng

AU - Liu, Shenyuan

AU - Yin, He

AU - Chen, Chang

AU - Wu, Yuru

AU - Qiu, Wei

AU - Mandich, Mirka

AU - Li, Hongyu

AU - Ademola, Adedasola

AU - Zhang, Chengwen

AU - Zeng, Chujie

AU - Jia, Xinlan

AU - Wang, Weikang

AU - Yuan, Haoyu

AU - Jiang, Huaiguang

AU - Tan, Jin

AU - Liu, Yilu

PY - 2021

Y1 - 2021

N2 - Large-scale power systems exhibit more complex dynamics due to the increasing integration of inverter-based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide-Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large-scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra-high density synchrophasor and point-on-wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)-based advanced applications are introduced, including AI-based inertia estimation, AI-based disturbance size and location estimation, AI-based system stability assessment, and AI-based data authentication.

AB - Large-scale power systems exhibit more complex dynamics due to the increasing integration of inverter-based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide-Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large-scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra-high density synchrophasor and point-on-wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)-based advanced applications are introduced, including AI-based inertia estimation, AI-based disturbance size and location estimation, AI-based system stability assessment, and AI-based data authentication.

KW - artificial intelligence

KW - inverter-based renewables

KW - situational awareness

KW - smart grid

KW - wide-area measurement system

UR - https://www.scopus.com/pages/publications/85117860112

U2 - 10.1049/hve2.12157

DO - 10.1049/hve2.12157

M3 - Article

AN - SCOPUS:85117860112

SN - 2397-7264

VL - 6

SP - 924

EP - 937

JO - High Voltage

JF - High Voltage

IS - 6

ER -

Adding Power of Artificial Intelligence to Situational Awareness of Large Interconnections Dominated by Inverter-Based Resources

Abstract

Bibliographical note

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Keywords

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