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Automating Substation Modeling Using Labeled Images

Madhusoodhanan, Arjun Kumar ORCID iD icon 1; Hoffmann, Julian ORCID iD icon 1; Schmidt, Pascal Emanuel 2; Schott, Marco 2; Kühnapfel, Uwe 1; Hagenmeyer, Veit ORCID iD icon 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)
2 Fakultät für Informatik (INFORMATIK), Karlsruher Institut für Technologie (KIT)

Abstract:

This paper presents a comprehensive workflow for automating substation modeling using labeled aerial images. Our approach streamlines the process into three key steps: generating the input dataset as labeled images, inferring an electrical substation model based on standard design principles and exemplarily importing the model into DIgSILENT PowerFactory as a simulation environment. We demonstrate that this new automated process significantly enhances speed, improves consistency, and facilitates easier updation of models, outperforming traditional manual methods.


Originalveröffentlichung
DOI: 10.1109/ICRERA62673.2024.10815180
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2024
Sprache Englisch
Identifikator ISBN: 979-83-503-7558-9
KITopen-ID: 1000177733
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Erschienen in 13th International Conference on Renewable Energy Research and Applications (ICRERA), 9th - 13th November 2024, Nagasaki, Japan
Veranstaltung 13th International Conference on Renewable Energy Research and Applications (ICRERA 2024), Nagasaki, Japan, 09.11.2024 – 13.11.2024
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 1050–1054
Schlagwörter Labeled Images, Powerfactory API, Electrical Substation Model, Automation.
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