Estimate measurement errors of household water meters using a large amount of on-site data feedback

Autor: Hsin-Liang Chen, Shang-Lien Lo, Jeff Kuo, Chin-Ling Huang
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Sustainable Environment Research, Vol 33, Iss 1, Pp 1-9 (2023)
Druh dokumentu: article
ISSN: 2468-2039
DOI: 10.1186/s42834-023-00180-z
Popis: Abstract Water meter measurement error is considered as one important component of non-revenue water by International Water Association. Its magnitude depends combinedly on users’ consumption behaviors (intake spectrum) and metrological characteristics of water meters (meter error curve). Most published researches have only analyzed the meter error curves without taking the users’ consumption behaviors into consideration. This study developed a practical approach by using the relative difference chart of master-meters and sub-meters groupings (i.e., RM-μz chart) to identify average metering errors for a major water utility company in Taiwan. About 120,000 sets of “master-meter and sub-meter grouping” data of Taipei Water Department were analyzed. The approach successfully estimated average metering errors of its 99.6% domestic meters (around 1.6 million water meters), the results are 9.9, 6.1, and 10.0% less than the actual water consumption recorded by the sub-meters, master-meters, and direct-meters, respectively.
Databáze: Directory of Open Access Journals