2026-08-03T15:39:10Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:21364 2024-10-28T08:50:38Z ddc:004 open_access

Improving Power System Resilience with Enhanced Monitoring, Control, and Protection Algorithms Veerakumar, Nidarshan Boričić, Aleksandar Tyuryukanov, Ilya Tealane, Marko Naglič, Matija Van Riet, Maarten Klaar, Danny Jongepier, Arjen Bos, Jorrit Golshani, Mohammad Rietveld, Gert van der Meijden, Mart Popov, Marjan Grid Resilience Synchrophasors Real-time Cyber-Physical Experimental Testbed Real-Time Monitoring Protection and Control Event Detection Classification Artificial Intelligence Adaptive Incremental Learning Controlled Islanding Vulnerability State Estimation Dynamic Line and Cable Rating This paper deals with the essentials of synchrophasor’s applications for future power systems to increase system reliability and resilience, which have been investigated within a four-year research project. The project has several applications, covering real-time disturbance detection and blackout prevention distributed across multiple work-packages. Firstly, an advanced big-data management platform built in a real-time digital simulation (RTDS) environment is described to support measurement data collection, processing, and sharing among stakeholders. This platform further presents and demonstrates a network-splitting methodology to avoid cascading failures. Online generator coherency identification is another synchrophasor application implemented on the platform, the use of which is demonstrated in the context of controlled network splitting. Using synchrophasors, data-analytics techniques can also identify and classify disturbances in real time with minor human intervention. Therefore, a novel centralized artificial intelligence (AI) based expert system is outlined to detect and classify critical events. Finally, the paper elaborates on developing advanced system resilience metrics for real-time vulnerability assessment of power systems with a high penetration of renewable energy, focusing on increasingly relevant dynamic interactions and system instability risks. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Nidarshan Veerakumar and Aleksandar Boričić and Ilya Tyuryukanov and Marko Tealane and Matija Naglič and Maarten Van Riet and Danny Klaar and Arjen Jongepier and Jorrit Bos and Mohammad Golshani and Gert Rietveld and Mart van der Meijden and Marjan Popov 2024 Is Part Of OASIcs, Volume 124, Commit2Data (2024) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.Commit2Data.7 urn:nbn:de:0030-drops-213647 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Commit2Data.7 eng https://creativecommons.org/licenses/by/4.0/legalcode