Conference article

Appliances Facilitating Everyday Life - Electricity Use Derived from Daily Activities

Kajsa Ellegård
Dept of Thematic Studies, Linköping University, Sweden

Joakim Widén
Dept of Engineering Sciences, Uppsala University, Sweden

Katerina Vrotsou
Dept of Science and Technology, Linköping University, Sweden

Download articlehttp://dx.doi.org/10.3384/ecp110571031

Published in: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:37, p. 1031-1038

Show more +

Published: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

The purpose of this paper is to present how; using a visualization method; electricity use can be derived from the everyday activity patterns of household members. Target groups are; on the one hand; professionals in the energy sector and energy advisors who need more knowledge about household energy use; and; on the other hand; household members wanting to reduce the energy use by revealing their own habits and thereby finding out how changed activity performance may influence electricity use. The focus is on the relation between utilizing electric appliances to perform everyday life activities and the use of electricity. The visualization method is based on the time-geographic approach developed by Hägerstrand and includes a model that estimates appliance electricity use from household members’ activities. Focus; in this paper; is put on some basic activities performed to satisfy daily life needs: cooking and use of information; communication and entertainment devices. These activities appear frequently in the everyday life of households; even though not all household members perform them all. The method is applied on a data material comprising time-diaries written by 463 individuals (aged 10 to 85+) in 179 households in different parts of Sweden. The visualization method reveals when and for how long activities that claim electric appliances are performed by which individual(s). It also shows electricity load curves generated from the use of appliances at different levels; such as individual; household and group or population levels. At household level the method can reveal which household members are the main users of electricity; i.e. the division of labour between household members. Thereby it also informs about whom could be approached by energy companies and energy advisors in information campaigns. The main result of the study is that systematic differences in activity patterns in subgroups of a population can be identified (e.g. men and women) but that directed information based on these patterns has to be made with care and with the risk of making too broad generalizations.

Keywords

Electricity use; Everyday activity sequence; Visualization; Activity pattern; Load curve.

References

[1] Lindén; Anna-Lisa; Carlsson-Kanyama; Annika & Eriksson; B (2006); Efficient and inefficient aspects of residential energy behavior. What are the policy instruments of change”; Energy Policy; 34; 1918-1927. doi: 10.1016/j.enpol.2005.01.015.

[2] Lindén; Anna-Lisa (2007) Hushållens energianvändning och styrmedelsstrategier; Report ER 2007:41; Swedish Energy Agency; Eskilstuna; Sweden.

[3] Ellegård; Kajsa & Cooper; Matthew (2004) Complexity in daily life: A 3D visualisation showing activity patterns in their contexts. eIJTUR; 37; 37–59.

[4] Ellegård; Kajsa & Vrotsou; Katerina (2006) Capturing patterns of everyday life – presentation of the visualization method VISUAL-TimePAcTS; Paper presented at the IATUR Annual Conference 2006. Copenhagen.

[5] Vrotsou; Katerina; Ellegård; Kajsa & Cooper; Matthew (2009) Exploring time diaries using semi-automated activity pattern extraction. Electronic International Journal of Time Use Research 2009; Vol. 6; No. 1; 1-25. doi: 10.13085/eIJTUR.6.1.1-25.

[6] Ellegård; Kajsa; Vrotsou; Katerina & Widén; Joakim (2010) VISUAL-TimePAcTS/energy use – a software application for visualizing energy use from activities performed. Paper presented at the Scientific session; Energitinget; Stockholm Älvsjö Fairs. March 2010 (http://works.bepress.com/dr_erik_dahlquist/6/)

[7] Vrotsou; Katerina (2010) Everyday mining. Exploring sequences in event-based data. Linköping studies in Science and technology. Dissertations no 1331. Linköping University; Sweden

[8] Gram-Hanssen; Kirsten (2004) Different Everyday Lives – Different Patterns of Electricity Use. In: Proceedings of the 2004 American Council for an Energy Efficient Economy. Summer study in Buildings. Washington DC: ACEEE.

[9] Hägerstrand; Torsten (1974) Tidsgeografisk beskrivning - syfte och postulat. Svensk Geografisk Årsbok 50; 86-94.

[10] Hägerstrand; Torsten (1985) Time-Geography. Focus on the Corporeality of Man; Society and Environment. The Science and Praxis of Complexity. The United Nations University; Tokyo; pp 193-216. French translation in Science et pratique de la complexité La Documentation Francaise; Paris 1986; pp 225-250

[11] Hägerstrand; Torsten & Lenntorp; Bo (1993) Region och miljö - sammanfattning av ett projekt om ekologiska perspektiv på den rumsliga närings- och bosättningsstrukturen; NordREFO 1993:5. pp 229-237.

[12] Hägerstrand; Torsten (2009) Tillvaroväven. (K Ellegård & U Svedin Eds). Forskningsrådet Formas; Stockholm.

[13] Widén; Joakim (2009) Distributed Photovoltaics in the Swedish Energy System. Model Development and Simulations. Licentiate Thesis; Uppsala University; Sweden.

[14] Widén; Joakim (2010) System Studies and Simulations of Distributed Photovoltaics in Sweden. PhD Thesis; Uppsala University; Sweden.

Citations in Crossref