A generic architecture for robust automatic detection and suppression of sub-harmonics
Autor(en): | Hülsmann, J. Buschermöhle, A. Lintze, C. Brockmann, W. |
Herausgeber: | Horbach, M. | Stichwörter: | Harmonic analysis; Social computing, Automatic Detection; Critical issues; Generic architecture; Power grids; Prony analysis; Signal quality; Subharmonics, Electric power transmission networks | Erscheinungsdatum: | 2013 | Herausgeber: | Gesellschaft fur Informatik (GI) | Journal: | Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI) | Volumen: | 220 | Startseite: | 1455 | Seitenende: | 1469 | Zusammenfassung: | Sub-harmonic phenomena become a critical issue as properties of the power grid change. In this paper we propose a generic architecture to detect and suppress these sub-harmonics automatically in a robust way. Therefore different algorithms to analyse the signals from the power grid, like wavelet- and prony analysis, are used and extended to rate and incorporate signal quality. The results of these algorithms are dynamically fused using according to their trustworthiness in order to achieve a detection as robust as possible. Afterwards the intervention needed to suppress a detected sub-harmonic is determined and applied by remote load management in our case. First experimental results show the validity of this trustworthiness-based architecture. © 2013 Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI). |
Beschreibung: | Conference of 43. Jahrestagung der Gesellschaft fur Informatik e.V. ,GI, Informatik Angepasst an Mensch, Organisation und Umwelt, Informatik 2013 - 43rd Annual Meeting of the German Informatics Society (GI), Computer Science Adapting to Individuals, Organizations and Environment, Informatics 2013 ; Conference Date: 16 September 2013 Through 20 September 2013; Conference Code:158761 |
ISBN: | 9783885796145 | ISSN: | 16175468 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083220395&partnerID=40&md5=96ed1a9a77c7e67d1e938a2423dccccb |
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geprüft am 01.06.2024