• 07.08.2020  Industrial excess heat for district heating: Database shows great potential for supplying households

    Excess heat from energy-intensive industries is often suitable for use in district heating systems but is usually unutilized. A detailed overview of the potentials available in the EU is now provided by a database of the sEEnergies project. In Germany, 29 petajoules of excess heat from industrial sites could be used, which corresponds to the demand of more than half a million households. The information is available as maps and downloadable datasets.


 Fraunhofer Institute for Systems and Innovation Research (ISI)


Institute for Resource Efficiency and Energy Strategies


      TEP Energy GMBH

Load profiles for the household sector – accounting for heterogeneity


4th European Conference on Behaviour and Energy Efficiency (Behave 2016)

Recent studies have pointed out that the household sector’s heterogeneity is not reflected in the currently used standard load profiles, and can therefore lead to misjudgements when used in energy system modelling. To improve sector-specific evaluations within the eLOAD model, we developed a set of representative household profiles, which were presented and discussed at the Behave 2016 conference. The load profiles were compiled using cluster analysis of smart-meter data based on hourly electricity consumption with household characteristics as the explanatory variables. Hourly data from 561 households were used in this study. We found significant differences in the temporal courses of the representative load profiles. A subsequent statistical analysis revealed that household size, employment, average age and the presence of children are distinguishing factors for the different types of households. Stereotypical names were given to the household types for illustration purposes (see figure below). These results suggest that (i) the residential sector is not well represented by a single standard load profile and (ii) different household types can be identified using socio-demographic characteristics.

Load profiles for the household sector – accounting for heterogeneity

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