Real-time demand estimation and confidence limit analysis for water distribution systems

Doosun Kang, Kevin E Lansey

Research output: Contribution to journalArticle

68 Citations (Scopus)

Abstract

A real-time estimation of water distribution system state variables such as nodal pressures and chlorine concentrations can lead to savings in time and money and provide better customer service. While a good knowledge of nodal demands is prerequisite for pressure and water quality prediction, little effort has been placed in real-time demand estimation. This study presents a real-time demand estimation method using field measurement provided by supervisory control and data acquisition systems. For real-time demand estimation, a recursive state estimator based on weighted least-squares scheme and Kalman filter are applied. Furthermore, based on estimated demands, real-time nodal pressures and chlorine concentrations are predicted. The uncertainties in demand estimates and predicted state variables are quantified in terms of confidence limits. The approximate methods such as first-order second-moment analysis and Latin hypercube sampling are used for uncertainty quantification and verified by Monte Carlo simulation. Application to a real network with synthetically generated data gives good demand estimations and reliable predictions of nodal pressure and chlorine concentration. Alternative measurement data sets are compared to assess the value of measurement types for demand estimation. With the defined measurement error magnitudes, pipe flow data are significantly more important than pressure head measurements in estimating demands with a high degree of confidence.

Original languageEnglish (US)
Pages (from-to)825-837
Number of pages13
JournalJournal of Hydraulic Engineering
Volume135
Issue number10
DOIs
StatePublished - 2009

Fingerprint

limit analysis
Water distribution systems
Chlorine
chlorine
SCADA systems
Pipe flow
Measurement errors
Kalman filters
Water quality
water distribution system
demand
pipe flow
Kalman filter
Sampling
estimation method
prediction
data acquisition
savings
water quality

Keywords

  • Estimation
  • Least squares method
  • Limit analysis
  • Uncertainty principles
  • Water distribution systems

ASJC Scopus subject areas

  • Water Science and Technology
  • Civil and Structural Engineering
  • Mechanical Engineering

Cite this

Real-time demand estimation and confidence limit analysis for water distribution systems. / Kang, Doosun; Lansey, Kevin E.

In: Journal of Hydraulic Engineering, Vol. 135, No. 10, 2009, p. 825-837.

Research output: Contribution to journalArticle

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