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Towards Cognitive Assistance and Prognosis Systems in Power Distribution Grids - Open Issues, Suitable Technologies, and Implementation Concepts

Gitzel, Ralf; Hoffmann, Martin W.; Heiden, Philipp Zur; Skolik, Alexander; Kaltenpoth, Sascha; Kaltenpoth, Sascha; Müller, Oliver; Kanak, Cansu; Kandiah, Kajan; Stroh, Max-Ferdinand; Boos, Wolfgang; Zajadatz, Maurizio ORCID iD icon 1; Suriyah, Michael 2; Leibfried, Thomas 1; Singhal, Dhruv Suresh 3; Bürger, Moritz; Hunting, Dennis; Rehmer, Alexander; Boyaci, Aydin
1 Institut für Elektroenergiesysteme und Hochspannungstechnik (IEH), Karlsruher Institut für Technologie (KIT)
2 Karlsruher Institut für Technologie (KIT)
3 Institut für Technische Mechanik (ITM), Karlsruher Institut für Technologie (KIT)

Abstract:

In recent times, both geopolitical challenges and the need to counteract climate change have led to an increase in generated renewable energy as well as an increased demand for clean electrical energy. The resulting variability of electricity production and demand as well as an overall demand increase, put additional stress on the existing grid infrastructure. This leads to strongly increased maintenance demands for distribution system operators (DSOs). Today, condition monitoring is used to address these challenges. Researchers have already explored solutions for monitoring critical assets like switchgear and circuit breakers. However, with a shrinking knowledgeable technical workforce and increasing maintenance requirements, mere monitoring is insufficient. Already today, DSOs ask for actionable recommendations, optimization strategies, and prioritization methods to manage the growing task backlog effectively. In this paper we propose a vision of a grid-level cognitive assistance system that translates the outcome of diagnosis and prognosis systems into actionable work tasks for the grid operator. The solution is highly interdisciplinary and based on empirical studies of real-world requirements. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000173561
Veröffentlicht am 27.08.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Elektroenergiesysteme und Hochspannungstechnik (IEH)
Institut für Technische Mechanik (ITM)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2169-3536
KITopen-ID: 1000173561
Erschienen in IEEE Access
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Band 12
Seiten 107927–107943
Nachgewiesen in Dimensions
Web of Science
Scopus
Globale Ziele für nachhaltige Entwicklung Ziel 7 – Bezahlbare und saubere EnergieZiel 13 – Maßnahmen zum Klimaschutz
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