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A common strategy for leakage reduction in Water Distribution Networks (WDNs) is the use of Pressure Reducing Valves (PRVs). As well known, a relationship between pressure and water losses can be established, according to which reducing pressure results in reduced losses. In many cases pressure is greater than the minimum required for adequate service level, because of the variability of flow and pressure within the WDN. To increase the effectiveness of PRVs, a Real Time Control (RTC) of the regulated pressure can be developed, as pointed out by many researchers. Consequently, in the paper the issues arising from pressure RTC in a WDN is discussed. Laboratory experiments were carried out to assess the capability of the controller to achieve the set point pressure, regardless of the inlet conditions. A numerical model was also developed, showing good agreement with experiments.

In hydraulic systems, water is often pumped to reach higher elevations, so as to ensure the minimum required pressure and guarantee adequate service level. However, pumps cannot be instantly activated and people do not consume the resource in uniform mode throughout the day. To avoid direct pumping, water can be stored in tanks at a higher elevation, so that it can be supplied whenever there is a higher demand. Because of the significant costs required for pumping, energy-saving in water supply systems is one of the most challenging issues to ensure optimal management of water systems. Careful scheduling of pumping operations may lead not only to energy savings, but alsoto prevent damages, as consequence of reduction of operation times and switches. By means of computer simulation, an optimal schedule of pumps can be achieved using optimization algorithms. In this paper, a harmony-search multi-objective (HSMO) optimization approach is adapted to the pump scheduling problem. The model interfaces with the popular hydraulic solver, EPANET 2.0, to check the hydraulic constraints and to evaluate the performances of the selected schedules. Penalties are introduced in the objective function in case of violation of the hydraulic constraints. The model is applied to a case study, showing that the results are comparable with those of competitive meta-heuristic algorithms (e.g. Genetic Algorithms) and pointing out the suitability of the HSMO algorithm for pumping optimization.