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  Data-driven load profiles and the dynamics of residential electricity consumption

Anvari, M., Proedrou, E., Schäfer, B., Beck, C., Kantz, H., Timme, M. (2022): Data-driven load profiles and the dynamics of residential electricity consumption. - Nature Communications, 13, 4593.
https://doi.org/10.1038/s41467-022-31942-9

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 Creators:
Anvari, Mehrnaz1, Author              
Proedrou, Elisavet2, Author
Schäfer, Benjamin2, Author
Beck, Christian2, Author
Kantz, Holger2, Author
Timme, Marc2, Author
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Abstract: The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. Here, we analyse highly resolved residential electricity consumption data of Austrian, German and UK households and propose a generally applicable data-driven load model. Specifically, we disentangle the average demand profiles from the demand fluctuations based purely on time series data. We introduce a stochastic model to quantitatively capture the highly intermittent demand fluctuations. Thereby, we offer a better understanding of demand dynamics, in particular its fluctuations, and provide general tools for disentangling mean demand and fluctuations for any given system, going beyond the standard load profile (SLP). Our insights on the demand dynamics may support planning and operating future-compliant (micro) grids in maintaining supply-demand balance.

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Language(s): eng - English
 Dates: 2022-08-062022-08-06
 Publication Status: Finally published
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41467-022-31942-9
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Working Group: Dynamics, stability and resilience of complex hybrid infrastructure networks
Research topic keyword: Energy
Research topic keyword: Nonlinear Dynamics
Regional keyword: Europe
MDB-ID: pending
OATYPE: Gold Open Access
 Degree: -

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Project name : CoNDyNet2
Grant ID : 03EF3055F
Funding program : -
Funding organization : BMBF
Project name : Gefördert im Rahmen des Förderprogramms "Open Access Publikationskosten" durch die Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 491075472.
Grant ID : -
Funding program : Open-Access-Publikationskosten (491075472)
Funding organization : Deutsche Forschungsgemeinschaft (DFG)

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Title: Nature Communications
Source Genre: Journal, SCI, Scopus, p3, oa
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Pages: - Volume / Issue: 13 Sequence Number: 4593 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals354
Publisher: Nature