Leak Detection and Localization through Demand Components Calibration

Abstract

Success in the application of any model-based methodology (e.g., design, control, supervision) highly depends on the availability of a well-calibrated model. The calibration of water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). This work proposes a leak-detection and localization approach to be coupled with a calibration methodology that identifies geographically distributed parameters. The approach proposed consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows unexpected behavior of the calibrated parameters (e.g., abrupt changes, trends, etc.) to be associated with a specific zone in the network. The performance of the methodology proposed is tested on a real water distribution network using synthetic data. Tested scenarios include leaks occurring at different locations and ranging from 2.5 to 13% of the total consumption. Leakage is represented as pressure-dependent demand simulated as emitter flows at the network nodes. Results show that even considering a low number of sensors, leaks with an effect on parameters higher than the parameters’ uncertainty can be correctly detected and located within 200 m.