Citation:

Shao, Y., S. Chu, T. Zhang, J. Yang, AND T. Yu. A Greedy Sampling Design Algorithm for the Modal Calibration of Nodal Demand in Water Distribution Systems. Mathematical Problems in Engineering. Hindawi Publishing Corporation, New York, NY, 2019:3917571, (2019). https://doi.org/10.1155/2019/3917571

Impact/Purpose:

This journal article describes a newly developed technical approach for sensor placement to effectively conduct distribution network calibration and modeling. The results can help water utilities in water distribution management and thus in better SDWA compliance.

Description:

This paper presents a greedy optimization algorithm for sensor placement to calibrate a water distribution system (WDS) hydraulic model more efficiently. The proposed approach improves the calibration accuracy by optimizing sensor placement. An optimally located sensor not only obtains its own monitoring information, but also infers the condition of other nodes. Based on this principle, we have proposed a greedy algorithm for better calibration accuracy and modeling efficiency. The mathematical approach is based on the product of the calibration deviation vector and pressure weight coefficient vector, in a stepwise sensor placement scheme. The robustness of the proposed approach is tested under different spatial and temporal demand distribution. We found that both the number of sensors and the perturbation ratio affect the calibration accuracy as defined by the average nodal pressure deviation itself and its variability. The plot of the calibration accuracy versus the number of sensors can reasonably guide the trade-off between model calibration accuracy and number of sensors placed or the cost. This proposed approach is superior in calibration accuracy and time consumed when compared to the standard genetic algorithm (SGA) and Monte Carlo Sampling algorithm (MCS).

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