Node search space reduction for optimal placement of pressure sensors in water distribution networks for leakage detection
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Date
2024-03
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Publisher
Elseviere
Abstract
This study presents a methodological framework for optimal placement of pressure sensors in Water Distribution
Networks (WDNs) for leakage monitoring under uncertainty. Monte Carlo simulation is utilized to simulate
leakages of different magnitudes at various nodes in the WDN taking into consideration background noise and
minimum resolution of pressure sensors. A novel sensor preselection algorithm based on community detection
and maximum entropy computation to reduce the search space of the pressure Sensor Placement Problem (SPP)
is presented. The pressure SPP is formulated as a multi-objective optimization problem that seeks to maximize
Joint Entropy, Coverage, and minimize Total Correlation. NSGA-II is used to solve the SPP and the solutions in
the optimal Pareto front are ranked using a hybrid Entropy TOPSIS to eliminate potential bias and subjective
human judgement in optimal sensor configuration implementation. The sensor preselection algorithm achieved a
67% reduction in the search space (possible sensor positions) of the case study, C-TOWN WDN, with only 2.78%
reduction in coverage. The result of the pressure SPP indicates only 21 pressure sensors are needed to cover
95.45% of the WDN under study. Finally, the overall performance of the proposed methodological framework is
presented and compared with other related works.
Description
This article is published by Elsevier, 2024 and also available at https://doi.org/10.1016/j.aej.2024.03.037
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Citation
Alexandria Engineering Journal 94 (2024) 325–338