An Approach to Disaggregating Total Household Water Consumption into Major End-Uses
- 447 Downloads
The aim of this project is to assign domestic water consumption to different devices based on the information provided by the water meter. We monitored a sample of Barcelona and Murcia with flow switches that recorded when a particular device was in use. In addition, the water meter readings were recorded every 5 and 1 s, respectively, in Barcelona and Murcia. The initial work used Barcelona data, and the method was later verified and adjusted with the Murcia data. The proposed method employs an algorithm that characterizes the water consumption of each device, using Barcelona to establish the initial parameters which, afterwards, provide information for adjusting the parameters of each household studied. Once the parameters have been adjusted, the algorithm assigns the consumption to each device. The efficacy of the assignation process is summarized in terms of: sensitivity and specificity. The algorithm provides a correct identification rate of between 70 % and 80 %; sometimes even higher, depending on how well the chosen parameters reflect household consumption patterns. Considering the high variability of the patterns and the fact that use is characterized by only the aggregate consumption that the water meter provides, the results are quite satisfactory.
KeywordsWater pattern recognition Use of water Domestic consumption Water profile Water disaggregation
The authors are grateful to R + I Alliance for the financial support that made it possible to develop this project. The authors are also grateful to AQUAGEST SOLUTONS for their very useful comments and suggestions during the preparation of this manuscript.
- Casella G, Berger LR (2001) Principle of data reduction. In: Thomson Learning (ed) Statistical inference, 2nd edn., United States, pp 271–310Google Scholar
- Eurostat (2007) Consumers in Europe – Facts and figures on services of general interest http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-DY-07-001/EN/KS-DY-07-001-EN.PDF. Accessed 16 April 2012
- Fontdecaba S, Grima P, Marco L, Rodero L, Sánchez-Espigares J, Solé I, Tort-Martorell X, Demessence D, Martínez De Pablo V, Zubelzu J (2012) A methodology to model water demand based on the identification of homogenous client segments. Application to the city of Barcelona. Water Resources Management 26:499–516. doi: 10.1007/s11269-011-9928-5 CrossRefGoogle Scholar
- Mayer WP, William B, DeOreo TE, Lewis DM (2003) Residential indoor water conservation study: evaluation of high efficiency indoor plumbing fixture retrofits in single-family homes in the East BayMunicipal Utility District Service Area. Prepared to East BayMunicipal Utility District and The United States Environmental Protection AgencyGoogle Scholar
- Tong YL (1989) The multivariate normal distribution. Springer Series in Statistics, 1st edn., United StatesGoogle Scholar
- Yamagami S, Nakamura H (1996) Non-intrusive submetering of residential gas appliances. ACEEE Summer Study on Energy Efficiency in Buildings, 265-273Google Scholar