The DeMaDs Open Source Modeling Framework for Power System Malfunction Detection

David Fellner (Speaker), Thomas Strasser, Wolfgang Kastner

    Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review

    Abstract

    Modeling and simulation of electrical power systems are becoming increasingly important approaches for the development and operation of novel smart grid functionalities - especially with regard to data-driven applications as data of certain operational states or misconfigurations can be next to impossible to obtain. The DeMaDs framework allows for the simulation and modeling of electric power grids and malfunctions therein. Furthermore, it serves as a testbed to assess the applicability of various data -driven malfunction detection methods. These include data mining techniques, traditional machine learning approaches as well as deep learning methods. The framework's capabilities and functionality are laid out here, as well as explained by the means of an illustrative example.
    Original languageEnglish
    Title of host publicationProceedings
    Place of PublicationAachen, Germany
    Number of pages6
    ISBN (Electronic)979-8-3503-1122-8
    DOIs
    Publication statusPublished - 5 Apr 2023
    Event2023 Open Source Modelling and Simulation of Energy Systems (OSMSES) - RWTH Aachen, Aachen, Germany
    Duration: 27 Mar 202329 Mar 2023
    https://go.fzj.de/osmses2023

    Conference

    Conference2023 Open Source Modelling and Simulation of Energy Systems (OSMSES)
    Abbreviated titleOSMSES
    Country/TerritoryGermany
    CityAachen
    Period27/03/2329/03/23
    Internet address

    Research Field

    • Power System Digitalisation

    Keywords

    • Data-driven approach
    • malfunction detection
    • modeling and simulation
    • electric power systems
    • smart grids

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