A probabilistic approach for detection and classification of PRV malfunctions in the water distribution network of the city of Patras in western Greece 

<p>Effective management of water losses in water distribution networks (WDNs) still remains a demanding task, as the temporal and spatial variability of water resources under changing climatic conditions and the increasing needs for drinking water may lead to freshwater shortages. In this context, pressure management strategies are widely adopted in an effort to reduce the water losses in the supply and distribution parts of water networks and, consequently, deescalate their environmental footprint. Installation of pressure reducing valves (PRVs) at critical locations of WDNs plays a central role in pressure regulation strategies, as PRVs reduce the upstream pressure to a set outlet pressure (i.e., downstream of the PRV), usually referred to as set point. Perdios et al. (2022) developed a novel statistical framework and applied it to an existing pressure management area (PMA) of the city of Patras in western Greece, aiming at early detection of PRV malfunctions that may significantly influence network&#8217;s operation and the corresponding lifetime of related infrastructure. The results showed that the suggested methodology allows reliable detection of critical malfunctions at least 2 days prior to flow disruptions. &#921;n this study, we calibrate and implement Perdios et al. (2022) statistical framework, using pressure data for a 4-year period from 01/Jan./2017 to 26/Nov./2020 from several important PMAs of the WDN of the city of Patras, aiming towards better understanding of the causes of the malfunctions, by decomposing the observed pressure deviations from the set point to systematic and random error components.</p> <p><strong>Acknowledgements </strong></p> <p>The research work has been conducted within the project PerManeNt, which has been 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 &#8211; CREATE &#8211; INNOVATE (project code: T2EDK-04177).</p> <p><strong>Reference</strong></p> <p>Perdios A., G. Kokosalakis, N. Th. Fourniotis, I. Karathanasi and A. Langousis (2022) Statistical framework for the detection of pressure regulation malfunctions and issuance of alerts in water distribution networks, <em>Stoch. Env. Res. Risk Asses.</em>, https://doi.org/10.1007/s00477-022-02256-5</p>