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    Smart Meter Analytics to Pinpoint Opportunities for Reducing Household Water Use

    Source: Journal of Water Resources Planning and Management:;2016:;Volume ( 142 ):;issue: 006
    Author:
    Rachel Cardell-Oliver
    ,
    Jin Wang
    ,
    Helen Gigney
    DOI: 10.1061/(ASCE)WR.1943-5452.0000634
    Publisher: American Society of Civil Engineers
    Abstract: Knowledge of when, how, and by whom water is being used is crucial for planning ways to conserve drinking water. The goal of this paper is to identify groups of similar households (whom) based on their regular high-magnitude behaviors (RHMBs) of water consumption (when and how). RHMBs are frequent recurrences of high water use with regular timing. Household RHMBs are promising targets for behavior change. A two-stage data analytics approach is proposed. First, smart meter data is analyzed to identify RHMBs automatically. Second, salient features of the RHMBs are used to group households with similar behaviors. The approach is evaluated on two contrasting towns from low-rainfall regions of Australia. RHMBs accounted for 2 to 10 times more water than the traditional water efficiency target of continuous flows. For one group of 220 households, 60% of peak-hour demand was RHMBs. This paper demonstrates how RHMBs can be used to pinpoint opportunities for tailored demand management. Targets for substantial reductions in water consumption and supply costs are identified.
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      Smart Meter Analytics to Pinpoint Opportunities for Reducing Household Water Use

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    http://yetl.yabesh.ir/yetl1/handle/yetl/82399
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    contributor authorRachel Cardell-Oliver
    contributor authorJin Wang
    contributor authorHelen Gigney
    date accessioned2017-05-08T22:32:51Z
    date available2017-05-08T22:32:51Z
    date copyrightJune 2016
    date issued2016
    identifier other49127341.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/82399
    description abstractKnowledge of when, how, and by whom water is being used is crucial for planning ways to conserve drinking water. The goal of this paper is to identify groups of similar households (whom) based on their regular high-magnitude behaviors (RHMBs) of water consumption (when and how). RHMBs are frequent recurrences of high water use with regular timing. Household RHMBs are promising targets for behavior change. A two-stage data analytics approach is proposed. First, smart meter data is analyzed to identify RHMBs automatically. Second, salient features of the RHMBs are used to group households with similar behaviors. The approach is evaluated on two contrasting towns from low-rainfall regions of Australia. RHMBs accounted for 2 to 10 times more water than the traditional water efficiency target of continuous flows. For one group of 220 households, 60% of peak-hour demand was RHMBs. This paper demonstrates how RHMBs can be used to pinpoint opportunities for tailored demand management. Targets for substantial reductions in water consumption and supply costs are identified.
    publisherAmerican Society of Civil Engineers
    titleSmart Meter Analytics to Pinpoint Opportunities for Reducing Household Water Use
    typeJournal Paper
    journal volume142
    journal issue6
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0000634
    treeJournal of Water Resources Planning and Management:;2016:;Volume ( 142 ):;issue: 006
    contenttypeFulltext
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