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An Efficient Approach for Nodal Water Demand Estimation in Large-scale Water Distribution Systems

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Abstract

Real-time modeling of a water distribution system (WDS) is a critical step for the control and operation of such systems. The nodal water demand, as the most important time-varying parameter, must be estimated in real time. The computational burden of nodal water demand estimation is intensive, leading to inefficiency in the modeling of large-scale networks. The Jacobian matrix computation and Hessian matrix inversion are the main processes that dominate the computation time. To address this problem, an approach for shortening the computation time for real-time demand estimation in large-scale network is proposed. This approach allows the Jacobian matrix to be efficiently computed based on solving a system of linear equations, and a Hessian matrix inversion method based on matrix partitioning and the iterative Woodbury-Matrix-Identity Formula is proposed. The developed approach is applied to a large-scale network, in which the number of nodal water demands is 12523, and the number of measurements ranges from 10 to 2000. The results show that the time consumptions for the Jacobian computation and Hessian matrix inversion are within 465.3 ms and 1219.0 ms, respectively. The time consumption is significantly shortened compared with the existing approach, especially for nodal water demand estimation in large-scale WDSs.

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All data, models, and codes that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 52070165).

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Authors and Affiliations

  1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058, China

    Shipeng Chu, Tuqiao Zhang, Xinhong Zhou, Tingchao Yu & Yu Shao

Authors
  1. Shipeng Chu
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  2. Tuqiao Zhang
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  3. Xinhong Zhou
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  4. Tingchao Yu
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  5. Yu Shao
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Contributions

Shipeng Chu: Conceptualization, Methodology, Software, Validation, Writing-Original Draft. Tuqiao Zhang: Writing-Review & Editing, Resources, Project administration. Xinhong Zhou: Visualization, Investigation, Formal analysis. Tingchao Yu: Writing - Review & Editing.Yu Shao: Writing - Review & Editing, Supervision, Funding acquisition.

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Correspondence to Yu Shao.

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Chu, S., Zhang, T., Zhou, X. et al. An Efficient Approach for Nodal Water Demand Estimation in Large-scale Water Distribution Systems. Water Resour Manage 36, 491–505 (2022). https://doi.org/10.1007/s11269-021-03024-w

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