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Leakages in water distribution systems (WDS) can lead to supply interruptions, contaminations and economic losses. Hence finding leaks before they cause severe problems is a crucial task for water utilities. To identify the existence of leaks, night flow measurements in district-metered areas (DMA) are common practice. Therefore, the entire system has to be subdivided in hydraulically separated partial networks. However, many utilities do not want to lose the hydraulic redundancy of their system and hence search for other solutions to identify and allocate leaks. In our research, the effects of leakages on the hydraulic behaviour of WDS are utilized to find the optimal solution for placing hydraulic sensors. From the discrepancy of the unperturbed and the perturbed WDS due to the occurrence of leakage, a methodology is developed which enables an efficient placement of flow meters and pressure sensors. This is achieved by a Fault Sensitivity Matrix (FSM). Finding the optimal position of a minimum number of sensors is carried out by a specific Genetic Algorithm called Differential Evolution (DE). DE is chosen due to its good rate of convergence reducing the computation time. This is of special interest for large WDS. Once an optimal sensor placement is obtained, DE is also used for leakage localization. The methodology has been applied and tested in two different WDS. The first WDS was a model network published by Poulakis in 2003. The second was a partial network of an Austrian city. Here the task was to place as few sensors as possible concerning economical costs while guaranteeing leakage localization in an area of a predefined size. In this paper it is shown that DE performs well, both on sensor placement and leakage localization, for both investigated systems. Additionally the implementation of demand and measurement uncertainties is outlined.


Session R58, Water Distribution Networks: Leak Detection II



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