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dc.contributor.authorKuusela Pirkko;Norros Ilkka;Reittu Hannu;Piira Kalevi
dc.date.accessioned2019-02-26T07:57:52Z
dc.date.available2019-02-26T07:57:52Z
dc.date.issued2018
dc.identifier.other%28ASCE%29EY.1943-7897.0000532.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4250568
dc.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.
dc.publisherAmerican Society of Civil Engineers
dc.titleHierarchical Multiplicative Model for Characterizing Residential Electricity Consumption
dc.typeJournal Paper
dc.journal.volume144
dc.journal.issue3
dc.journal.titleJournal of Energy Engineering
dc.identifier.doi10.1061/(ASCE)EY.1943-7897.0000532
dc.page4018023
dc.treeJournal of Energy Engineering:;2018:;Volume ( 144 ):;issue: 003
dc.contenttypeFulltext


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