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Automated Household Water End-Use Disaggregation through Rule-Based Methodology

TitoloAutomated Household Water End-Use Disaggregation through Rule-Based Methodology
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2021
AutoriMazzoni, F., Alvisi S., Franchini M., Ferraris M., and Kapelan Z.
RivistaJournal of Water Resources Planning and Management
Volume147
ISSN07339496
Parole chiaveBologna, Disaggregation, Domestic water use, Efficient managements, Household water, Italy, Knowledge based systems, methodology, Residential sectors, Rule based, Smart meters, Temporal resolution, Water distribution systems, water economics, water footprint, water management, water planning, water supply, water use efficiency
Abstract

Application of smart meters to the residential sector can provide insight into where and when water is used, thereby enabling utilities to achieve an efficient management of water distribution systems. Moreover, detailed information about domestic water use can be obtained by disaggregating smart meter data collected at the household inlet point. In this paper, a rule-based, automated methodology for disaggregating household water-use data into end uses is presented. The methodology is applicable to 1-min temporal resolution data, whose granularity is slightly lower than the one generally used in other methodologies, potentially allowing it to be applied to several contexts in the field of water-use monitoring. The methodology was set up and validated with data collected for 2 months through intrusive monitoring of four households in Bologna, Italy, and represents a pioneering case in which disaggregation performance is directly assessed by the comparison against data collected at each end use. The results obtained showed that the methodology enables household water use to be efficiently disaggregated even if detailed information about end-use features is not available. © 2021 American Society of Civil Engineers.

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85103042161&doi=10.1061%2f%28ASCE%29WR.1943-5452.0001379&partnerID=40&md5=e12595448e767f345d8ee7b9d7409748
DOI10.1061/(ASCE)WR.1943-5452.0001379
Citation KeyMazzoni2021