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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.

Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 09.11.2024
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.
Nachgewiesen in Dimensions
OpenAlex
Scopus

Originalveröffentlichung
DOI: 10.1109/ICRERA62673.2024.10815180
Seitenaufrufe: 57
seit 08.01.2025
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