Location and Setting Optimization of the Pressure Reducing Valves in Urban Water Networks to Pressure Management and Leakage Reduction

Given the varying water demand for various hours of the day from different seasons, the pressure of the water distribution network (WDN) will vary at different times. In the event of a decrease in demand, the network pressure increases, and the excess pressure leads to increase the leakage from old connections and small fractures. One of the ways to reduce leakage is the network pressure management and reduce excess pressure, which it can be achieved by the pressure reducing valves.‏ But the question is, how many pressure reducing valves and at which points of the water network should be installed. In the first part of this study, the optimal location of the pressure reducing valves (PRV's) was found by the combination of the binary genetic optimization algorithm (GA) and real differential evolution (DE) optimization algorithm. For this purpose, the GA proposes the potential locations (pipes) for the valve installation to the DE algorithm, and it attempts to eliminate surplus head in the WDN by making changes in the Hazen-William coefficient of proposed pipes and creating a head loss on the pipes. These changes should be in such a way that the WDN's constraints like the minimum allowable pressure to be respected. The related hybrid algorithm was coded in MATLAB software and connected to the Epanet software as a hydraulic solver. After determining the hydraulic model of the water network and the number of PRVs by the designer, the proposed code determines the optimal installation location of the PRVs in order to the reduction of network background leakage. In the next part of the study, after determining the optimal location of the PRVs, the optimal set-point of each PRVs has been determined. To this end, a single objective differential evolution algorithm is used. The design variable of the optimization algorithm is the outlet pressure of the installed PRVs and the permissible pressure ratio on both sides of PRVs considered as a new network constraint alongside the minimum allowable pressure. The objective function of this optimization problem is minimizing of WDN's background leakage. After validating of presented codes, they applied on a local WDN in the north of IRAN, Guilan, entitled Mehr Water Network. The covered area of this network is 144 acres and its daily average demand is 366 m3 per hour. The altitude difference of Mehr WDS is about 4 meters and it has 371 pipes with the length of 33 kilometers, 366 junctions, one reservoir and a pump station with 3 pumps. Results show that installing two pressure reducing valves in determined locations and control them with DE optimization algorithm can reduce the surplus head and background water leakage from 21.9% to 12.3% (about 41.3%) On a full day. It is noteworthy that this method can be used in Supervisory control and data acquisition (SCADA) in order to pressure management of WDNs and leakage reduction. A calibrated hydraulic model of WDN, current state of valves and pumps and demand multiplier (obtained from installed flow meters or estimated demand profile) are required as the input of the optimization code to determine the optimum output pressure (set-point) of PRVs in SCADA telecontrol system.