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    Hierarchical Multiplicative Model for Characterizing Residential Electricity Consumption

    Source: Journal of Energy Engineering:;2018:;Volume ( 144 ):;issue: 003
    Author:
    Kuusela Pirkko;Norros Ilkka;Reittu Hannu;Piira Kalevi
    DOI: 10.1061/(ASCE)EY.1943-7897.0000532
    Publisher: American Society of Civil Engineers
    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.
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      Hierarchical Multiplicative Model for Characterizing Residential Electricity Consumption

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4250568
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    contributor authorKuusela Pirkko;Norros Ilkka;Reittu Hannu;Piira Kalevi
    date accessioned2019-02-26T07:57:52Z
    date available2019-02-26T07:57:52Z
    date issued2018
    identifier other%28ASCE%29EY.1943-7897.0000532.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4250568
    description abstractThis 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.
    publisherAmerican Society of Civil Engineers
    titleHierarchical Multiplicative Model for Characterizing Residential Electricity Consumption
    typeJournal Paper
    journal volume144
    journal issue3
    journal titleJournal of Energy Engineering
    identifier doi10.1061/(ASCE)EY.1943-7897.0000532
    page4018023
    treeJournal of Energy Engineering:;2018:;Volume ( 144 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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