Water use signature patterns for analyzing household consumption using medium resolution meter data

被引:41
|
作者
Cardell-Oliver, Rachel [1 ,2 ]
机构
[1] Univ Western Australia, CRC Water Sensit Cities, Crawley, WA 6009, Australia
[2] Univ Western Australia, Sch Comp Sci & Software Engn, Crawley, WA 6009, Australia
关键词
water conservation; residential water use; information discovery; smart metering; water resources; ELECTRICITY CONSUMPTION;
D O I
10.1002/2013WR014458
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Providers of potable water to households and businesses are charged with conserving water. Addressing this challenge requires accurate information about how water is actually being used. So smart meters are being deployed on a large scale by water providers to collect medium resolution water use data. This paper presents water use signature patterns, the first technique designed for medium resolution meters for discovering patterns that explain how households use water. Signature patterns are clusters (subsets) of water meter readings specified by patterns on volumes and calendar dates. Four types of signature pattern are introduced in this paper: continuous flow days; exceptional peak use days; programmed patterns with recurrent hours; and normal use partitioned by season and period of the day. Signature patterns for each household are calculated using efficient selection rules that scale for city populations and years of data collection. Data from a real-world, large-scale, smart metering trial are analyzed using water use signature patterns. The results demonstrate that water use behaviors are distinctive, for both individuals and populations. Signatures can identify behaviors that are promising targets for water conservation. Pattern discovery can be automated with an efficient and scalable computer program. By identifying relevant consumption patterns in medium resolution meter data, water use signature patterns can help to achieve the water conservation potential of large-scale smart metering.
引用
收藏
页码:8589 / 8599
页数:11
相关论文
共 50 条
  • [21] Electricity Consumption Clustering Using Smart Meter Data
    Tureczek, Alexander
    Nielsen, Per Sieverts
    Madsen, Henrik
    ENERGIES, 2018, 11 (04)
  • [22] ANALYZING DISAGGREGATE FRESH VEGETABLE AND FRUIT CONSUMPTION FROM HOUSEHOLD SURVEY DATA
    HUANG, CL
    HOUSTON, JE
    AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS, 1994, 76 (05) : 1276 - 1276
  • [23] High Resolution Residential Domestic Hot Water Consumption Profiles Using Data Mining Clustering Techniques on Time of Use Data
    Buttitta, Giuseppina
    Finn, Donal
    SUSTAINABILITY IN ENERGY AND BUILDINGS 2018, 2019, 131 : 159 - 168
  • [24] Mining Residential Household Information from Low-resolution Smart Meter Data
    Fusco, Francesco
    Wurst, Michael
    Yoon, Ji Won
    2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012), 2012, : 3545 - 3548
  • [25] Comparative multiple regression analysis of household electricity use in Latvia: using smart meter data to examine the effect of different household characteristics
    Laicane, Ilze
    Blumberga, Dagnija
    Blumberga, Andra
    Rosa, Marika
    INTERNATIONAL SCIENTIFIC CONFERENCE ENVIRONMENTAL AND CLIMATE TECHNOLOGIES, CONECT 2014, 2015, 72 : 49 - 56
  • [26] Analysis of spatiotemporal household water consumption patterns and their relationship with meteorological variables
    Niazmardi, Saeid
    Sadrykia, Mansoureh
    Rezazadeh, Mahdi
    URBAN CLIMATE, 2023, 52
  • [27] Household Energy Consumption Segmentation Using Hourly Data
    Kwac, Jungsuk
    Flora, June
    Rajagopal, Ram
    IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (01) : 420 - 430
  • [28] A Subspace Signature Based Approach for Residential Appliances Identification Using Less Informative and Low Resolution Smart Meter Data
    Dinesh, H. G. C. P.
    Nettasinghe, D. B. W.
    Godaliyadda, G. M. R. I.
    Ekanayake, M. P. B.
    Wijayakulasooriya, J. V.
    Ekanayake, J. B.
    2014 9TH INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS (ICIIS), 2014, : 605 - 610
  • [29] Residential electricity consumption and household characteristics: An econometric analysis of Danish smart-meter data
    Andersen, F. M.
    Gunkel, P. A.
    Jacobsen, H. K.
    Kitzing, L.
    ENERGY ECONOMICS, 2021, 100
  • [30] Analysis of Advanced Meter Infrastructure Data of Water Consumption in Apartment Buildings
    Kermany, Einat
    Mazzawi, Hanna
    Baras, Dorit
    Naveh, Yehuda
    Michaelis, Hagai
    19TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (KDD'13), 2013, : 1159 - 1167