Hierarchical Multiplicative Model for Characterizing Residential Electricity Consumption

    Research output: Contribution to journalArticleScientificpeer-review

    2 Citations (Scopus)
    42 Downloads (Pure)

    Abstract

    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.
    Original languageEnglish
    Number of pages14
    JournalJournal of Energy Engineering
    Volume144
    Issue number3
    Early online date15 Mar 2018
    DOIs
    Publication statusPublished - Mar 2018
    MoE publication typeA1 Journal article-refereed

    Keywords

    • Household electricity consumption
    • mathematical modeling
    • clustering
    • profiles
    • monitoring

    Fingerprint Dive into the research topics of 'Hierarchical Multiplicative Model for Characterizing Residential Electricity Consumption'. Together they form a unique fingerprint.

    Cite this