Optimization of pumping schedule based on forecasting the hourly water demand in Seoul

In modern water distribution systems, pumping accounts for a large portion of the costs; therefore, water utilities need to reduce the pumping cost. The purpose of this study was to reduce and optimize the pumping costs. The study area was composed of one filtration plant, five reservoirs and 3 pumping stations. The IP (Integer programming) method used for the optimization, as it gave a global solution, with the pump controlled as either on or off. It is necessary to correctly forecast the hourly water demand to obtain an IP solution as both the optimized pumping schedule and low limitation of the reservoir are dependent on this factor. Therefore, three methods (time index, multiple regression + time index & Fourier series + transfer ARIMA) were compared to forecast the hourly water demand. As a result of these comparisons, the multiple regression + time index model was selected. The low limitation of the reservoir was also determined depending on the correction of the hourly water demand model. The optimization of pumping in the water distribution system had previously been simulated for 3 months using the IP. As a result of this simulation, it was found that the pumping cost could be reduced by 12.2%∼38.7%.