Interactive decision support methodology for near real-time response to failure events in a water distribution network

Abstract

The present study proposes a new interactive methodology and an interactive tool for the response to water network failure events facilitating near real-time decision-making. The proposed methodology considers (i) a structured yet flexible approach supporting and guiding the operator throughout the entire response process to water network failure events, while allowing the operator to have a final say; (ii) a novel interaction with the operator in near real time via the proposed tool (e.g. allowing operators to propose different ‘what-if’ scenarios without being hydraulic experts); (iii) the provision of automatically generated advices (e.g. optimal response solutions and assessed end-impacts) – although optimal response solutions not identified in near real time yet and (iv) improved impact assessment using realistic impact indicators that cover different aspects of the event – which are consistently calculated for every proposed response solution (to facilitate easy comparison between different response solutions). The new methodology was applied on a semi-real case study. The results obtained demonstrated the potential of the new response methodology and its application through the interactive tool to improve water utilities' current practice. This was accomplished through supporting/guiding operators in the identification of effective response solutions with low end-impact on the consumers and low cost for the utility.

Optimization-Based Selection of Hydrants and Valves Control in Water Distribution Networks for Fire Incidents Management

“…Mahmoud et al [7] proposed a methodology for the real-time control of burst incidents. Control during burst incidents was also studied by Kapelan et al [8] and Nikoloudi et al [9]. In all these cases the authors made use of genetic algorithms.…”

Automatic Network Response Methodology for Failure Recovery or Bursts in Drinking Water Networks

“…Besides, in Mahmoud et al (2018), the selection of the optimal interventions among a preestablished subset is posed as a multiobjective optimization solved using a genetic algorithm that returns the Pareto optimal curve of intervention strategies. Recently, Nikoloudi et al (2021) uses a similar approach as the core of a new interactive real-time decision-making tool for the response to failures in water distribution networks. Their tool is based on several steps covering stages like: initial impact assessment, identification of the isolation plan, identification of the response solution, and solution impact assessment.…”

Artificial intelligence underpins urban water infrastructure of the future: A holistic perspective

“…In water distribution systems, the deployment of online leakage detection and decision support tools can help pinpoint leaks (Zhou et al, 2019;Zaman et al, 2020;Wang et al, 2020b) and contamination event detection (Arad et al, 2013), and thus reduce the impacts of failure (Romano et al, 2014;Nikoloudi et al, 2021) through rapid interventions even before water services are affected. Machine learning can identify key factors of pipe failure related to infrastructure, operation and environmental factors, and thus help develop strategies for predictive maintenance (Barton et al, 2022).…”