Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources
Article
Article Title | Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources |
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ERA Journal ID | 212697 |
Article Category | Article |
Authors | Zhu, Lin (Author), Zhao, Yinfeng (Author), Cui, Yi (Author), You, Shutang (Author), Yu, Wenpeng (Author), Liu, Shengyuan (Author), Yin, He (Author), Chen, Chang (Author), Wu, Yuru (Author), Qiu, Wei (Author), Mandich, Mirka (Author), Li, Hongyu (Author), Ademola, Adedasola (Author), Zhang, Chengwen (Author), Zeng, Chujie (Author), Jia, Xinlan (Author), Wang, Weikang (Author), Yuan, Haoyu (Author), Jiang, Huaiguang (Author), Tan, Jin (Author) and Liu, Yilu (Author) |
Journal Title | High Voltage |
Journal Citation | 6 (6), pp. 924-937 |
Number of Pages | 14 |
Year | 2021 |
Publisher | The Institution of Engineering and Technology |
Place of Publication | United Kingdom |
ISSN | 2397-7264 |
Digital Object Identifier (DOI) | https://doi.org/10.1049/hve2.12157 |
Web Address (URL) | https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/hve2.12157 |
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 | Advanced applications; Complex dynamics; Inverter-based; Large-scale power systems; Large-scales; Monitoring and control; Power; Sensors data; Situational awareness; Synchrophasor measurements |
ANZSRC Field of Research 2020 | 460207. Modelling and simulation |
400803. Electrical energy generation (incl. renewables, excl. photovoltaics) | |
460308. Pattern recognition | |
Byline Affiliations | University of Tennessee, United States |
National Renewable Energy Laboratory, United States | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q7w01/adding-power-of-artificial-intelligence-to-situational-awareness-of-large-interconnections-dominated-by-inverter-based-resources
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High Voltage - 2021 - Zhu - Adding power of artificial intelligence to situational awareness of large interconnections.pdf | ||
License: CC BY-NC 4.0 | ||
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