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Monitoring Electricity Demand Synchronization Using Copulas

Gebhard, Tobias ; Steinke, Florian ; Brucherseifer, Eva (2022)
Monitoring Electricity Demand Synchronization Using Copulas.
IEEE PES Innovative Smart Grid Technology (ISGT Europe 2022). Novi Sad, Serbia (10.10.2022-12.10.2022)
doi: 10.1109/ISGT-Europe54678.2022.9960369
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Synchronization of the behavior of residential consumers, for example during crises, can lead to overloads in electric power grids. This holds especially for distribution grids, where the electrical infrastructure is not designed for the simultaneous high consumption of all households. Therefore, the monitoring and detection of (upcoming) synchronization trends is important. It is the basis for any countermeasures. We propose to model the dependency structure of consumer demands with a Gaussian copula using its correlation parameter as an indicator for synchronization. We then analyze the probability distribution of the aggregated load depending on the synchronization indicator. This allows us to infer the synchronization parameter from load measurements in real-time using a Bayesian approach. In simulation experiments with realistic household consumption distributions, we show how increased synchronization can be detected.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2022
Autor(en): Gebhard, Tobias ; Steinke, Florian ; Brucherseifer, Eva
Art des Eintrags: Bibliographie
Titel: Monitoring Electricity Demand Synchronization Using Copulas
Sprache: Englisch
Publikationsjahr: 28 November 2022
Verlag: IEEE
Buchtitel: Proceedings of 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)
Veranstaltungstitel: IEEE PES Innovative Smart Grid Technology (ISGT Europe 2022)
Veranstaltungsort: Novi Sad, Serbia
Veranstaltungsdatum: 10.10.2022-12.10.2022
DOI: 10.1109/ISGT-Europe54678.2022.9960369
Kurzbeschreibung (Abstract):

Synchronization of the behavior of residential consumers, for example during crises, can lead to overloads in electric power grids. This holds especially for distribution grids, where the electrical infrastructure is not designed for the simultaneous high consumption of all households. Therefore, the monitoring and detection of (upcoming) synchronization trends is important. It is the basis for any countermeasures. We propose to model the dependency structure of consumer demands with a Gaussian copula using its correlation parameter as an indicator for synchronization. We then analyze the probability distribution of the aggregated load depending on the synchronization indicator. This allows us to infer the synchronization parameter from load measurements in real-time using a Bayesian approach. In simulation experiments with realistic household consumption distributions, we show how increased synchronization can be detected.

Freie Schlagworte: emergenCITY_CPS
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Energieinformationsnetze und Systeme (EINS)
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Forschungsfelder
Forschungsfelder > Energy and Environment
Forschungsfelder > Energy and Environment > Integrated Energy Systems
Hinterlegungsdatum: 19 Dez 2022 10:02
Letzte Änderung: 15 Aug 2023 10:02
PPN: 510636756
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