Aplicação de modelos de otimização na operação de sistemas elevatórios em redes de abastecimento de água

Water supply systems are fundamental to society and are increasingly being demanded in terms of quantity and quality of water. In addition to these two aspects, which are the basis of the service provided, other issues have generated a lot of pressure, environmental preservation, the quality of service from companies, and costs to consumers. The improvement in the provision of the service and the reduction of costs necessarily involves the improvement of the system’s operation. The energy cost of pumping is one of the factors that most affect the operating cost of the systems. The relevance of the cost of energy with pumping motivated this work. Through computational modeling, we sought to minimize the costs of a real pumping system. Nonlinear programming and the genetic algorithms of the Excel solver tool were applied to obtain the optimal cost of pumping. The decision variables of the model were the 24-hour pump operation intervals. The main restrictions are to respect the limits of the reservoirs and the recovery of levels at the end of the 24-hour cycle. Both techniques were able to find viable solutions, however, the evolutionary algorithms confirmed their slowness in relation to the generalized reduced gradient (GRG). In both techniques, peak hours were minimally allocated to the operation. Regarding the studied system, it was found that the main responsible for the operational cost is the transport of water treatment plants (WTP) to R5, approximately 81,69%, and there is a limitation in the pumping capacity that prevents the complete shutdown of the pumps during peak hours. In the present study, the following specific consumptions were obtained: elevatory station EE 1 (ETA-R5) 0.897kWh/m³; EE 2 (R5-R4) 0.16 kWh/m³; EE 3 (R4-RLS) 0.617037 kWh/m³ and EE 4 (R4-RC) of 0.471852 kWh/m³. Considering the average of the subsystem studied, there are 0.537 kWh/m³, EE 2 (R5-R4) being more efficient, and less efficient EE 1 (ETA-R5). This can be justified by the greater demand and because it is necessary to operate at peak hours with high-powered pumps. Investment in improving the system is necessary to increase its energy efficiency and, consequently, reduce the high costs of the operation.