TY - GEN
T1 - Synchrophasor-based Applications to Enhance Electrical System Performance in the Netherlands
AU - Popov, M.
AU - Boricic, A.
AU - Veerakumar, Nidarshan
AU - Naglic, Matija
AU - Tyuryukanov, I.
AU - Tealane, M.
AU - Rueda, José L.
AU - van der Meijden, M.A.M.M.
AU - Palensky, P.
AU - More Authors, null
PY - 2022
Y1 - 2022
N2 - This paper deals with the essentials of synchrophasor applications for future power systems aimed at increasing system reliability and resilience. In this work, several applications are presented, covering real-time disturbance detection and blackout prevention. Firstly, an advanced big-data management platform built in real-time digital simulation (RTDS) environment to support measurement data collection, processing and sharing among stakeholders is described. With this platform, a network splitting methodology to avoid cascading failures is presented and demonstrated, which upon the occurrence of a disturbance successfully isolates the affected part to avoid catastrophic cascade system outage. Online generator coherency identification is another synchrophasor application implemented on the platform, whose use is demonstrated in the context of controlled network splitting. By using synchrophasors, data-analytics techniques can also be used for identifying and classifying different disturbances in real-time with the least human intervention. Therefore, a novel centralized artificial intelligence (AI) based expert system to detect and classify critical events is outlined. Finally, the paper elaborates on the development of advanced system resilience metrics for real-time vulnerability assessment, with a focus on increasingly relevant dynamic interactions between distribution and transmission systems.
AB - This paper deals with the essentials of synchrophasor applications for future power systems aimed at increasing system reliability and resilience. In this work, several applications are presented, covering real-time disturbance detection and blackout prevention. Firstly, an advanced big-data management platform built in real-time digital simulation (RTDS) environment to support measurement data collection, processing and sharing among stakeholders is described. With this platform, a network splitting methodology to avoid cascading failures is presented and demonstrated, which upon the occurrence of a disturbance successfully isolates the affected part to avoid catastrophic cascade system outage. Online generator coherency identification is another synchrophasor application implemented on the platform, whose use is demonstrated in the context of controlled network splitting. By using synchrophasors, data-analytics techniques can also be used for identifying and classifying different disturbances in real-time with the least human intervention. Therefore, a novel centralized artificial intelligence (AI) based expert system to detect and classify critical events is outlined. Finally, the paper elaborates on the development of advanced system resilience metrics for real-time vulnerability assessment, with a focus on increasingly relevant dynamic interactions between distribution and transmission systems.
KW - Phasor Measurement Units
KW - Real-Time Monitoring
KW - Algorithms
KW - Wide Area Monitoring and Protection
KW - Artificial intelligence
KW - Controlled Islanding
UR - https://www.researchgate.net/publication/363270228_Synchrophasor-based_Applications_to_Enhance_Electrical_System_Performance_in_the_Netherlands
M3 - Conference contribution
T3 - CIGRE Paris 2022
SP - 1
EP - 10
BT - Proceedings of the CIGRE Paris 2022 Conference
PB - Cigré
T2 - CIGRE Session 2022
Y2 - 28 August 2022 through 2 September 2022
ER -