mdh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Looking for Patterns in Residential Electricity Consumption
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Eastern European University, Lutsk, Ukraine. (Mathematics and Applied Mathematics)
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0003-4589-7045
2014 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 61, 1768-1771 p.Article in journal (Refereed) Published
Abstract [en]

Residential electricity consumption is an important part of general energy use. Its detailed investigation, however, requires rich empirical data, here the data of Swedish households. The individual consumption is a time series of readings at certain time intervals (hourly, every ten minutes, or every minute, say). Series exhibit patterns, in terms of which they may be compared, and it is desirable to model similarity. Classical statistical methods (correlation, factor, and cluster analyses) are presently used for this purpose; they have the advantage of being more explicit than the techniques of adaptive data analysis that may recently have become excessively popular. The present work is methodological, preceding any massive statistical analyses. Factor analysis allowed describing individual styles in terms of time intervals (during a day) of maximal variability. Cluster analysis was used for finding groups of days with similar patterns; the obtained clusters can help interpreting the results of other methods. Comparing two households requires comparing two sets of time series; correlation analysis quantified the similarity between them.

Place, publisher, year, edition, pages
2014. Vol. 61, 1768-1771 p.
Keyword [en]
Electricity consumption, Pattern, Pearson correlation, Geometric mean
National Category
Mathematics Probability Theory and Statistics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-27332DOI: 10.1016/j.egypro.2014.12.208ISI: 000375936100393Scopus ID: 2-s2.0-84922349085OAI: oai:DiVA.org:mdh-27332DiVA: diva2:782093
Conference
6th International Conference on Applied Energy, ICAE 2014; National Taiwan University of Science and TechnologyTaipei; Taiwan; 30 May 2014 through 2 June 2014
Available from: 2015-01-19 Created: 2015-01-19 Last updated: 2017-12-05Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Authority records BETA

Wallin, Fredrik

Search in DiVA

By author/editor
Mamchych, TetyanaWallin, Fredrik
By organisation
Educational Sciences and MathematicsFuture Energy Center
In the same journal
Energy Procedia
MathematicsProbability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 38 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf