Parameterizing residential water demand pulse models through smart meter readings. (June 2016)

• Record Type: Journal Article
• Authors: Creaco, Enrico; Kossieris, Panagiotis; Vamvakeridou-Lyroudia, Lydia; Makropoulos, Christos; Kapelan, Zoran; Savic, Dragan
• Is Part Of: Environmental modelling & software. Volume 80(2016:Jun.)
• Page Start: 33
• Page End: 40
• Publication Date: 2016-06
• Subjects: Water demand -- Demand pulses -- Intensity -- Duration -- Correlation -- Parameterization; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.02.019
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: This paper proposes a method for parameterizing the Poisson models for residential water demand pulse generation, which consider the dependence of pulse duration and intensity. The method can be applied to consumption data collected in households through smart metering technologies. It is based on numerically searching for the model parameter values associated with pulse frequencies, durations and intensities, which lead to preservation of the mean demand volume and of the cumulative trend of demand volumes, at various time aggregation scales at the same time. The method is applied to various case studies, by using two time aggregation scales for demand volumes, i.e. fine aggregation scale (1 min or 15 min) and coarse aggregation scale (1 day). The fine scale coincides with the time resolution for reading acquisition through smart metering whereas the coarse scale is obtained by aggregating the consumption values recorded at the fine scale. Results show that the parameterization method presented makes the Poisson model effective at reproducing the measured demand volumes aggregated at both time scales. Consistency of the pulses improves as the fine scale resolution increases. Highlights: Poisson generation models with correlated pulse intensity and duration. Parameterization aimed at preserving mean and cumulative trend of demand volumes. Multiple time aggregation scales. Smart metering readings used in applications. The higher is the smart metering accuracy, the more consistent are the generated pulses.