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 TanYilu Liu

Research output: Contribution to journalArticlepeer-review

5 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 languageAmerican English
Pages (from-to)924-937
Number of pages14
JournalHigh Voltage
Volume6
Issue number6
DOIs
StatePublished - 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.

NREL Publication Number

  • NREL/JA-5C00-80350

Keywords

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

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