A data-driven method for unsupervised electricity consumption characterisation at the district level and beyond

A bottom-up electricity characterisation methodology of the building stock at the local level is presented. It is based on the statistical learning analysis of aggregated energy consumption data, weather data, cadastre, and socioeconomic information. To demonstrate the validity of this methodology,...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Energy reports Jg. 7; S. 5667 - 5684
Hauptverfasser:	Mor, Gerard, Cipriano, Jordi, Martirano, Giacomo, Pignatelli, Francesco, Lodi, Chiara, Lazzari, Florencia, Grillone, Benedetto, Chemisana, Daniel
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.11.2021 Elsevier
Schlagworte:	Building-stock models Characterisation Data-driven Electricity Building-stock models Characterisation Data-driven Electricity
ISSN:	2352-4847, 2352-4847
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!