contributor author | Rachel Cardell-Oliver | |
contributor author | Jin Wang | |
contributor author | Helen Gigney | |
date accessioned | 2017-05-08T22:32:51Z | |
date available | 2017-05-08T22:32:51Z | |
date copyright | June 2016 | |
date issued | 2016 | |
identifier other | 49127341.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/82399 | |
description 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. | |
publisher | American Society of Civil Engineers | |
title | Smart Meter Analytics to Pinpoint Opportunities for Reducing Household Water Use | |
type | Journal Paper | |
journal volume | 142 | |
journal issue | 6 | |
journal title | Journal of Water Resources Planning and Management | |
identifier doi | 10.1061/(ASCE)WR.1943-5452.0000634 | |
tree | Journal of Water Resources Planning and Management:;2016:;Volume ( 142 ):;issue: 006 | |
contenttype | Fulltext | |