Efficient management of water supply systems is nowadays one of the most important challenges for water utilities. Common efficiency gains in such systems can be achieved by reducing the leakages and by reducing the energy consumption. For the case of minimization of energy consumption a new technique for sectorization and efficient pressure management is presented, based on water distribution modeling and optimization. The technique is applicable to situations when energy consumption reduction can be achieved by dividing a large Pressure Management Zone (PMZ) in smaller, but more efficient PMZs, or sectors. It consists of three steps: 1) An initial selection of areas of influence of existing water sources (e.g pumping stations) is obtained through tracer analysis; this analysis identifies a set of potential valves that can be used for creating sectors; 2) The sectors are determined through a model-based optimization (using Genetic Algorithm (GA)), by operation of isolation valves that lead to sectors’ configuration that minimizes energy consumption; 3) After creating the sectors a second stage optimization with pressure management in each sector is performed. The methodology has been applied to the case study of Milano under the framework of the EU-FP7 project ICeWater. The system of Milano is operated by Metropolitana Milanese S.p.A (MM) and supplies water to around 1.3 million inhabitants. The distribution network is supplied with groundwater by a total of 29 pumping stations with 101 pumps and currently functions as one large PMZ. Around 27,000 valves exist in the distribution network and can be used for the sectorization. A reduction in the number of feasible isolation valves used in the optimization process was performed with the tracer analysis. Initial results show that there is room for energy consumption reduction by applying the proposed sectorization approach.
Castro Gama, Mario E.; Quan, Pan; Jonoski, Andreja; and Chiesa, Carlo, "Model-Based Sectorization Of Water Distribution Networks For Increased Energy Efficiency" (2014). CUNY Academic Works.