Statistical methodology for PRV malfunction detection and alerting in Water Distribution Networks

As the outflow velocity from a pipe crack increases with increasing hydraulic pressure, pressure management concepts have been widely applied to reduce water losses in the delivering and distribution parts of water networks. In this context, pressure reducing valves (PRVs) have been commonly used to regulate pressures and therefore reduce water losses, in both water supply and water distribution networks, by reducing the upstream pressure to a set outlet pressure (i.e. downstream of the PRV), usually referred to as set point.

As all types of mechanical equipment, PRVs exhibit malfunctions affecting pressure regulation, which can be defined as events when the outlet pressure does not match the set point. These events can be classified in two categories: a) high frequency fluctuations around the set point, and b) prolonged systematic deviations from the set point. Since PRV malfunctions result in systematic or random deviations of the outlet pressure from the set point, their detection can be approached in a statistical context.

In this study, we develop a novel framework for detection of PRV malfunctions in water supply and water distribution networks, which uses: a) the root mean squared error (RMSE) as a proper statistical metric for monitoring the performance of a PRV by detecting individual malfunctions (i.e. malfunction occurrences) in the high-resolution pressure time series, and b) the hazard function concept to identify a proper duration of sequential events from (a) to issue alerts.

The suggested methodology is implemented using pressure data at 1-min temporal resolution from pressure management area “Diagora” of the water distribution network of the city of Patras (the third largest city in Greece), for a 3 year period from 01 January 2017 to 31 December 2019. The obtained results show that the developed statistical approach effectively detects major PRV malfunctions (as reported by the Municipal Water Supply Company and Sewerage of Patras, DEYAP), allowing it to be used for operational purposes.

Acknowledgments:

This research is co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T2EDK-4177).