Technical Papers
Jan 9, 2015

Inversion Model of Water Distribution Systems for Nodal Demand Calibration

Publication: Journal of Water Resources Planning and Management
Volume 141, Issue 9

Abstract

Nodal demand calibration of a water distribution system (WDS) is a process of adjusting the nodal demand in WDS models to make its predictions consisting with measurements, which is an inversion problem compared to the conventional forward computation. Most existing methods rely on performing forward computation repeatedly to calculate the sensitivity matrix or generate offspring for searching for optimal solutions. This paper develops an alternative framework, namely an inversion model, to directly calibrate the nodal demand. The model is constructed by separating the known and unknown variables in continuity and energy equations of WDS using the matrix decomposition method. Specifically, the measured and unmeasured nodal demand, nodal head, and pipe flow are taken as knows and unknowns, respectively. The nodal demands with similar user characteristics are grouped (i.e., aggregated) to make the model overdetermined, and the Gauss-Newton based iteration method is applied to solve the model. To evaluate the calibration results when observation errors are involved, the standard deviations of unknowns are calculated using first-order second-moment method for uncertainty quantification, and the results are verified by Monte Carlo simulation. A simple network is used to illustrate the model construction in detail, and two numerical case studies, including a real highly looped network, are applied to further validate its effectiveness and feasibility. Encouraging results obtained clearly demonstrate the proposed method has potential for practical application in real-time nodal demand calibration, state estimation, and uncertainty quantification of WDSs.

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Acknowledgments

The authors would like to thank the editor and anonymous reviewers for the helpful comments on the paper. This work supported by “The national science and technology plan project of the 12th five-year of China (2012BAJ25B06)”.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 141Issue 9September 2015

History

Received: May 14, 2014
Accepted: Dec 2, 2014
Published online: Jan 9, 2015
Discussion open until: Jun 9, 2015
Published in print: Sep 1, 2015

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Authors

Affiliations

Du Kun, Ph.D. [email protected]
Faculty of Civil Engineering, Kunming Univ. of Science and Technology, Kunming 650500, China. E-mail: [email protected]
Long Tian-Yu [email protected]
Professor, Key Laboratory of the Three Gorges Reservoir Area Ecological Environment, Chongqing Univ., Chongqing 400045, China (corresponding author). E-mail: [email protected]
Wang Jun-Hui [email protected]
Master Student, Key Laboratory of the Three Gorges Reservoir Area Ecological Environment, Chongqing Univ., Chongqing 400045, China. E-mail: [email protected]
Guo Jin-Song [email protected]
Professor, Chongqing Institute of Green Intelligent Technology, Chinese Academy of Sciences, Chongqing 400045, China. E-mail: [email protected]

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