Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources. Issue 6 (24th October 2021)

• Record Type: Journal Article
• Authors: Zhu, Lin; Zhao, Yinfeng; Cui, Yi; You, Shutang; Yu, Wenpeng; Liu, Shengyuan; Yin, He; Chen, Chang; Wu, Yuru; Qiu, Wei; Mandich, Mirka; Li, Hongyu; Ademola, Adedasola; Zhang, Chengwen; Zeng, Chujie; Jia, Xinlan; Wang, Weikang; Yuan, Haoyu; Jiang, Huaiguang; Tan, Jin; Liu, Yilu
• Is Part Of: High voltage. Volume 6:Issue 6(2021)
• Page Start: 924
• Page End: 937
• Publication Date: 2021-10-24
• Subjects: High voltages -- Periodicals; 621.3191
• DOI: 10.1049/hve2.12157
• Languages: English
• ISSNs: 2397-7264

Abstract

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.