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,...

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Bibliographic Details

Published in:	Energy reports Vol. 7; pp. 5667 - 5684
Main Authors:	Mor, Gerard, Cipriano, Jordi, Martirano, Giacomo, Pignatelli, Francesco, Lodi, Chiara, Lazzari, Florencia, Grillone, Benedetto, Chemisana, Daniel
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2021 Elsevier
Subjects:	Building-stock models Characterisation Data-driven Electricity Building-stock models Characterisation Data-driven Electricity
ISSN:	2352-4847, 2352-4847
Online Access:	Get full text
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