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Operational concepts for the deployment of AI-supported maintenance strategies at Distribution System Operators to enable the energy and mobility transition

  • Climate change is leading to massive changes, especially in the areas of energy and mobility. As a connecting element of the energy and mobility transition, electricity grids will play a key role. Bidirectional energy flows and massive fluctuation in generation and consumption patterns lead to high stresses on components and systems, especially in the distribution grid. This confronts Distribution System Operators (DSOs) with new challenges to continue to ensure security of supply in an economical and resource-efficient manner. New maintenance strategies can enable operators to address these challenges. Novel sensors and artificial intelligence enable the technical use of methods such as Predictive Maintenance to detect and predict the probability of failure of critical components based on current condition data. Whereas Predictive Maintenance is already being used in many areas of the manufacturing industry today, the procedures are still new in operating medium-voltage switchgear in the distribution grid, which are critical for ensuring the security of supply. Today's maintenance processes are not automated and are based on Preventive Maintenance strategies and differ very much from those of production environments. For example, the used IT-systems differ as well as the level of involvement of service contractors and regulative requirements and limitations. The use of Predictive Maintenance in the operation of critical infrastructures therefore places special demands on existing maintenance strategies at DSOs to economically ensure security of supply. This paper proposes an operational concept consisting of a process model, IT-system landscape and information logistics model compatible with the current process and system architecture to deploy new maintenance strategies at DSOs.
Metadaten
Author:Kajan KandiahORCiD, Lars Frehen, Max-Ferdinand StrohORCiD, Volker StichORCiDGND
DOI:https://doi.org/10.15488/13479
ISSN:2701-6277
Parent Title (English):Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 - 1
Publisher:publish.Ing
Place of publication:Hannover
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2025/08/19
Date of first Publication:2023/04/20
Release Date:2025/08/19
Tag:02
AI; Artificial intelligence; Climate change; Distribution system operator; Energy transition; Mobility transition; Operating concepts
First Page:591
Last Page:599
Note:
AProSys:
AI-driven assistance and prognosis systems for the sustainable deployment in the intelligent distribution grid

The aim of the research project 'AProSys' is to sustainably transform sensor-based condition monitoring into a cognitive assistance system with a focus on AI-based prognostics for application within the distribution grid in order to successfully shape the energy and mobility transition in Germany.

Acknowledgments:
The research in this paper is part of the project AproSys, funded by the German Federal Ministry for Economic Affairs and Climate Action (03EI6090B).

Duration: 01.01.2023 – 31.12.2025
Funding no.: 03EI6090B
Funding: Federal Ministry for Economic Affairs and Energy (BMWE)
Promoters: Projektträger Jülich (PtJ) – Forschungszentrum Jülich GmbH

Benefits for the target group:
In the project applied for, the transformation of the condition analysis into a cognitive assistance system is to be realized with a resource-efficient minimum use of sensors and the monitoring is to be extended to connected neighboring power engineering systems.

Project partners:
    ABB AG Forschungszentrum Deutschland, Ladenburg
    Institut für Elektroenergiesysteme und Hochspannungstechnik (IEH) des Karlsruher Instituts für Technologie (KIT), Karlsruhe
    Institut für Technische Mechanik, Institutsteil Dynamik/Mechatronik (ITM) des Karlsruher Instituts für Technologie (KIT), Karlsruhe
    Gruppe Intelligente Systeme und Maschinelles Lernen der Universität Paderborn (SICP), Paderborn
    Heimann Sensor GmbH, Dresden
    Lehrstuhl für Wirtschaftsinformatik, insb. Betriebliche Informationssysteme der Universität Paderborn (SICP), Paderborn
    Westfalen Weser Netz GmbH, Paderborn
Name of the conference:Conference on Production Systems and Logistics CPSL 2023
place of the conference:Querétaro, Mexico
Date of the conference:28.02.2023-02.03.2023
Institute / Department:FIR e. V. an der RWTH Aachen
Informationsmanagement
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften
Licence (German):License LogoCreative Commons – CC BY 3.0 DE – Namensnennung 3.0 Deutschland