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Publication: Optimisation of Fixed-Outlet and Flow-Modulated Pressure Reduction Measures in Looped Water Distribution Networks Constrained by Fire-Fighting Capacity Requirements

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  • Upload-Date 5. November 2021
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The publication includes the AVAT tool from STOP-IT. Pressure management is a pivotal component when reducing leakages from water distribution networks, and can be achieved by sub-dividing existing networks into partitions where the pressure can be reduced effectively. There is a need to develop methods that aid in the identification of cost-effective partitions for pressure reduction, while simultaneously verifying that the topological changes entailed in these solutions do not compromise reliability and (fire-fighting) capacity requirements, especially in systems where the capacity is ensured through looped networks. This paper presents a method that can be used to this end, in which a novel combination of hydraulic simulations and graph theory is used to determine the maximal potential for (dynamic and static) pressure reduction, and this is used as a constraint for multi-objective optimization of pressure reduction measures. Trondheim, Norway, has been used as a case study area, and it is demonstrated how the developed method aids in the process of achieving leakage reduction in Trondheim. The results for Trondheim show that an economically optimal solution for pressure management is predicted to lead to a reduction from 28 to 22% water loss volume, and furthermore that effective pressure management will rely heavily on active (dynamic) regulation in this particular system.

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https://stop-it-project.eu/wp-content/uploads/2020/04/stopit_color_188x160px.png 0 0 Zimmermann https://stop-it-project.eu/wp-content/uploads/2020/04/stopit_color_188x160px.png Zimmermann2021-11-05 13:17:502021-11-05 13:17:50Publication: Optimisation of Fixed-Outlet and Flow-Modulated Pressure Reduction Measures in Looped Water Distribution Networks Constrained by Fire-Fighting Capacity Requirements

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 740610. The publication reflects only the authors’ views and the European Union is not liable for any use that may be made of the information contained therein.
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