<div class="csl-bib-body">
<div class="csl-entry">Fellner, D., Strasser, T., & Kastner, W. (2023). The DeMaDs Open Source Modeling Framework for Power System Malfunction Detection. In <i>Proceedings: 2023 Open Source Modelling and Simulation of Energy Systems (OSMSES)</i>. 2023 Open Source Modelling and Simulation of Energy Systems (OSMSES), Aachen, Germany. https://doi.org/10.1109/OSMSES58477.2023.10089746</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/188036
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dc.description.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.
en
dc.language.iso
en
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dc.subject
Data-driven approach
en
dc.subject
electric power systems
en
dc.subject
malfunction detection
en
dc.subject
modeling and simulation
en
dc.subject
smart grids
en
dc.title
The DeMaDs Open Source Modeling Framework for Power System Malfunction Detection
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Austrian Institute of Technology, Austria
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dc.relation.isbn
979-8-3503-1122-8
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dc.relation.doi
10.1109/OSMSES58477.2023
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dc.relation.issn
979-8-3503-1123-5
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings: 2023 Open Source Modelling and Simulation of Energy Systems (OSMSES)
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tuw.relation.publisherplace
Aachen, Germany
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tuw.researchTopic.id
C4
-
tuw.researchTopic.id
I4
-
tuw.researchTopic.id
E3
-
tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.name
Climate Neutral, Renewable and Conventional Energy Supply Systems
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tuw.researchTopic.value
25
-
tuw.researchTopic.value
25
-
tuw.researchTopic.value
50
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tuw.publication.orgunit
E325-04 - Forschungsbereich Regelungstechnik und Prozessautomatisierung
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tuw.publication.orgunit
E191-03 - Forschungsbereich Automation Systems
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tuw.publication.orgunit
E325 - Institut für Mechanik und Mechatronik
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tuw.publication.orgunit
E191 - Institut für Computer Engineering
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tuw.publisher.doi
10.1109/OSMSES58477.2023.10089746
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dc.description.numberOfPages
6
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tuw.author.orcid
0000-0002-6415-766X
-
tuw.author.orcid
0000-0001-5420-404X
-
tuw.event.name
2023 Open Source Modelling and Simulation of Energy Systems (OSMSES)
en
dc.description.sponsorshipexternal
Austrian Research Promotion Agency (FFG)
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dc.relation.grantnoexternal
879017
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tuw.event.startdate
27-03-2023
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tuw.event.enddate
29-03-2023
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tuw.event.online
Hybrid
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tuw.event.type
Event for scientific audience
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tuw.event.place
Aachen
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tuw.event.country
DE
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tuw.event.presenter
Fellner, David
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tuw.event.track
Single Track
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wb.sciencebranch
Maschinenbau
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wb.sciencebranch
Informatik
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wb.sciencebranch
Elektrotechnik, Elektronik, Informationstechnik
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wb.sciencebranch.oefos
2030
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
2020
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wb.sciencebranch.value
25
-
wb.sciencebranch.value
50
-
wb.sciencebranch.value
25
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item.fulltext
no Fulltext
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item.grantfulltext
restricted
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.languageiso639-1
en
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item.openairetype
conference paper
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item.cerifentitytype
Publications
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crisitem.author.dept
TU Wien
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crisitem.author.dept
E325 - Institut für Mechanik und Mechatronik
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crisitem.author.dept
E640 - Vizerektorat Digitalisierung und Infrastruktur
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crisitem.author.orcid
0000-0002-6415-766X
-
crisitem.author.orcid
0000-0001-5420-404X
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crisitem.author.parentorg
E300 - Fakultät für Maschinenwesen und Betriebswissenschaften