This work presents a hierarchical multiplicative framework for modeling the energy consumption of households. The constituents of the model are a lognormally distributed annual consumption, an annual consumption profile at weekly resolution, a mean weekly consumption profile, and a multiplicative lognormally distributed random variation. Further, the annual and weekly profiles of households are shown to fall naturally into a small number of rather homogeneous groups, identified by the regular decomposition method. The framework is adapted to monitor and compare populations of electricity consumers. On the other hand, it provides a convenient way to produce synthetic traces of household energy consumption with similar stochastic properties as measured traces. It is also shown how additional household information can be utilized to predict both the annual consumption and the random variation of the consumption of a household.
|Number of pages||14|
|Journal||Journal of Energy Engineering|
|Early online date||15 Mar 2018|
|Publication status||Published - Mar 2018|
|MoE publication type||A1 Journal article-refereed|
- Household electricity consumption
- mathematical modeling