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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