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Smart Meter Analytics to Pinpoint Opportunities for Reducing Household Water Use

机译:智能水表分析可准确把握减少家庭用水的机会

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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. (C) 2016 American Society of Civil Engineers.
机译:了解何时,如何以及由谁使用水对规划节约饮用水的方式至关重要。本文的目的是根据用水量(何时以及如何)的常规高强度行为(RHMB)来识别相似家庭(whom)的组。 RHMB是经常性高耗水的经常发生。家用RHMB是有希望改变行为的目标。提出了一种两阶段的数据分析方法。首先,分析智能电表数据以自动识别RHMB。第二,RHMB的显着特征用于将行为相似的家庭进行分组。该方法在来自澳大利亚低雨量地区的两个截然不同的城镇进行了评估。 RHMB的用水量是连续流量的传统节水目标的2到10倍。对于一组220户家庭,高峰时段需求的60%是RHMB。本文演示了如何使用RHMB查明定制需求管理的机会。确定了大幅减少水消耗和供水成本的目标。 (C)2016年美国土木工程师学会。

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