Node search space reduction for optimal placement of pressure sensors in water distribution networks for leakage detection

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.