A cluster analysis of energy-consuming activities in everyday life

Flexible consumption in the household sector concerns individuals' daily choices and the routines that develop in their households. Targeting household-level energy consumption therefore requires an understanding of energy consumption in relation to individual household members' activity patterns. Individual time-diaries reveal when, for how long and where energy-related activities occur, permitting discussions of the temporal flexibility of these activities. Using multiple time-diaries (n = 6477) from a population reveals differences in activity patterns in larger groups and permits recorded activities to be clustered. Few explorative studies perform cluster analyses of energy-consuming activities in order to examine when and for how long these activities occur. When clustering is done, it is usually based on socio-economic factors, and not on the activities performed in sequence. This paper reports a time-geographically inspired cluster analysis based on when and for how long some activities requiring electricity are performed in the home by individuals in a population. The presented cluster analysis based on activities gives a new perspective to the discussion of flexible users and provides a basis for deeper analyses, for example, of whether activities are moveable in time for individuals, complementing cluster analysis based on other variables.;Flexible consumption in the household sector concerns individuals' daily choices and the routines that develop in their households. Targeting household-level energy consumption therefore requires an understanding of energy consumption in relation to individual household members' activity patterns. Individual time-diaries reveal when, for how long and where energy-related activities occur, permitting discussions of the temporal flexibility of these activities. Using multiple time-diaries (n = 6477) from a population reveals differences in activity patterns in larger groups and permits recorded activities to be clustered. Few explorative studies perform cluster analyses of energy-consuming activities in order to examine when and for how long these activities occur. When clustering is done, it is usually based on socio-economic factors, and not on the activities performed in sequence. This paper reports a time-geographically inspired cluster analysis based on when and for how long some activities requiring electricity are performed in the home by individuals in a population. The presented cluster analysis based on activities gives a new perspective to the discussion of flexible users and provides a basis for deeper analyses, for example, of whether activities are moveable in time for individuals, complementing cluster analysis based on other variables.;Flexible consumption in the household sector concerns individuals daily choices and the routines that develop in their households. Targeting household-level energy consumption therefore requires an understanding of energy consumption in relation to individual household members activity patterns. Individual time-diaries reveal when, for how long and where energy-related activities occur, permitting discussions of the temporal flexibility of these activities. Using multiple time-diaries (n=6477) from a population reveals differences in activity patterns in larger groups and permits recorded activities to be clustered. Few explorative studies perform cluster analyses of energy-consuming activities in order to examine when and for how long these activities occur. When clustering is done, it is usually based on socio-economic factors, and not on the activities performed in sequence. This paper reports a time-geographically inspired cluster analysis based on when and for how long some activities requiring electricity are performed in the home by individuals in a population. The presented cluster analysis based on activities gives a new perspective to the discussion of flexible users and provides a basis for deeper analyses, for example, of whether activities are moveable in time for individuals, complementing cluster analysis ased on other variables.;