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 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

Fingerprint

Dive into the research topics of 'The DeMaDs Open Source Modeling Framework for Power System Malfunction Detection'. Together they form a unique fingerprint.

Cite this