A clustering framework for residential electric demand profiles

Mayank Jain, Tarek Alskaif, Soumyabrata Dev

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

The availability of residential electric demand profiles data, enabled by the large-scale deployment of smart metering infrastructure, has made it possible to perform more accurate analysis of electricity consumption patterns. This paper analyses the electric demand profiles of individual households located in the city Amsterdam, the Netherlands. A comprehensive clustering framework is defined to classify households based on their electricity consumption pattern. This framework consists of two main steps, namely a dimensionality reduction step of input electricity consumption data, followed by an unsupervised clustering algorithm of the reduced subspace. While any algorithm, which has been used in the literature for the aforementioned clustering task, can be used for the corresponding step, the more important question is to deduce which particular combination of algorithms is the best for a given dataset and a clustering task. This question is addressed in this paper by proposing a novel objective validation strategy, whose recommendations are then cross-verified by performing subjective validation.

Original languageEnglish
Title of host publicationSEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728147017
DOIs
Publication statusPublished - Sep 2020
Event3rd International Conference on Smart Energy Systems and Technologies, SEST 2020 - Virtual, Istanbul, Turkey
Duration: 7 Sep 20209 Sep 2020

Publication series

NameSEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies

Conference

Conference3rd International Conference on Smart Energy Systems and Technologies, SEST 2020
CountryTurkey
CityVirtual, Istanbul
Period7/09/209/09/20

Keywords

  • Clustering framework
  • Dimensionality reduction
  • Electric demand profiles
  • Objective validation

Fingerprint Dive into the research topics of 'A clustering framework for residential electric demand profiles'. Together they form a unique fingerprint.

Cite this