Large‐scale power systems exhibit more complex dynamics due to the increasing inte-gration of inverter‐based resources(IBRs).Therefore,there is an urgent need to enhance the situational awareness capability for bett...Large‐scale power systems exhibit more complex dynamics due to the increasing inte-gration 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 appli-cations are introduced,including AI‐based inertia estimation,AI‐based disturbance size and location estimation,AI‐based system stability assessment,and AI‐based data authentication.展开更多
基金supported in part by the U.S.Department of Energy Solar Energy Technologies Office under Award 34231 and 34224supported in part by NSF EAGER:Program under award number 1839684+2 种基金Cyber‐Physical Systems(CPS)Program under award number 1931975supported by the Engineering Research Center Pro-gram of the National Science Foundation and the Department of Energy under NSF Award Number EEC‐1041877the CURENT Industry Partnership Program.This work was authored in part by the National Renewable Energy Labora-tory,operated by Alliance for Sustainable Energy,LLC,for the U.S.Department of Energy(DOE)under Contract No.DE‐AC36‐08GO28308.
文摘Large‐scale power systems exhibit more complex dynamics due to the increasing inte-gration 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 appli-cations are introduced,including AI‐based inertia estimation,AI‐based disturbance size and location estimation,AI‐based system stability assessment,and AI‐based data authentication.
