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  4. Learning Demonstrator for Anomaly Detection in Distributed Energy Generation
 
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April 7, 2022
Paper (Preprint, Research Paper, Review Paper, White Paper, etc.)
Title

Learning Demonstrator for Anomaly Detection in Distributed Energy Generation

Title Supplement
Paper for 12th Conference on Learning Factories 2022
Abstract
Machine learning based anomaly detection methods on process data can be used to secure critical infrastructure. The design and installation of these methods require detailed understanding of both the facilities and the machine learning methods. Therefore, they are mostly incomprehensible for non-experts and thus acting as a barrier hindering the fast spread of such technologies. This article presents the systematic development of a demonstrator which enables presentations of anomaly detection on the example of a simulated wind farm. The specially designed user-interface allows a comprehensive experience. This article documents the use of the demonstrator for experts experienced in energy systems which are interested in the application of machine learning algorithms.
Author(s)
Pelchen, Timo
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Thiele, Gregor
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Vick, Axel  
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Radke, Marcel
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Schade, David
AUCOTEAM GmbH, Department for Energy Industry, Berlin, Germany
Krüger, Jörg  
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Project(s)
Reaktive IT-Sicherheitsüberwachung automatisierter technischer Anlagen in KRITIS
Funder
Bundesministerium für Bildung und Forschung -BMBF-  
Conference
Conference on Learning Factories 2022  
Open Access
DOI
10.24406/publica-161
File(s)
SSRN-id4075252.pdf (4.21 MB)
Rights
CC BY
Language
English
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Keyword(s)
  • Anomaly Detection

  • Learning Factories

  • Distributed Energy Generation

  • Modelica

  • Functional Mock-up Interface

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