Abstrakt

A key aspect of the design of specific tariff structures is to identify and characterize homogeneous electricity consumption profiles. Recent research in residential electricity demand has explored load profile segmentation via cluster analysis combined with descriptive data from the dwelling and occupants, which has partly explained electricity load patterns and their underlying drivers but has failed to investigate any consumption heterogeneity among similar households. Thus, the aim of this paper is to reverse this approach and investigate the extent that households with similar characteristics have different electricity consumption patterns. This study combines population-based register data with hourly electricity consumption data for a sample of 67 Danish households. First, a homogenous household group is selected based on several indicators that signal vulnerability. The specific group under investigation is single-person, older, low-income households in detached housing. Second, K-means clustering is used to identify similarities and differences in consumption patterns. The results indicate four distinct vulnerable household profiles characterized by different start and end times of peak and off-peak times, peak intensities, and overall consumption, which vary across seasons. These profiles are discussed concerning the performance of everyday practices and the design of demand-side management strategies targeted at vulnerable households.
OriginalsprogEngelsk
Artikelnummer4713
TidsskriftEnergies
Vol/bind13
Udgave nummer18
ISSN1996-1073
DOI
StatusUdgivet - sep. 2020

Bibliografisk note

Funding Information:
Funding: This work was financed by the European Research Council (ERC) under project grant Gram-Hanssen/786643, eCAPE “New Energy Consumer Roles and Smart Technologies—Actors, Practices and Equality.” Conflicts of Interest: The authors declare no conflict of interest. The funder had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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