Data-driven load profiles and the dynamics of residential electricity consumption.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
06 08 2022
06 08 2022
Historique:
received:
14
10
2020
accepted:
11
07
2022
entrez:
6
8
2022
pubmed:
7
8
2022
medline:
10
8
2022
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 35933555
doi: 10.1038/s41467-022-31942-9
pii: 10.1038/s41467-022-31942-9
pmc: PMC9357012
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4593Informations de copyright
© 2022. The Author(s).
Références
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Nov;72(5 Pt 2):056133
pubmed: 16383714
Phys Rev Lett. 2013 Mar 29;110(13):138701
pubmed: 23581387
Sci Rep. 2019 Dec 27;9(1):19971
pubmed: 31882778
Nat Commun. 2020 Dec 11;11(1):6362
pubmed: 33311505