Ant-colony optimization of pumping schedule to minimize the energy cost using variable-speed pumps in water distribution networks

Abstract

Despite considerable pumping energy costs in pumping stations of water distribution networks (WDNs), there are not many studies offering pumping schedule in order to optimize pumping energy costs regarding the WDN design. This paper aims to focus on the optimization of the WDN pumping station schedule by means of variable-speed pump (VSP) and using a combination of the ant system iteration best algorithm (ASib) and EPANET2.0. In fact, the VSP is implemented to increase the flexibility of pumping station and obtain the pumping schedule with optimized energy cost as the water demand changes during a day. Given that vast search space in optimization process leads to a decrease in the quality of final results, in this study, two heuristic methods coupled with ASib are proposed in order to reduce the number of feasible solutions in the search space. The optimization results showed that the proposed heuristic approaches have considerably improved the quality of solutions produced by the ASib and enhanced the navigation of the optimization process. The results of optimization for the Richmond network, similar to the genetic algorithm (GA), showed that the ASib was capable of improving pumping energy costs. Besides, using the variable-speed pump in an optimized pump scheduling could lead to greater savings (about 10%) in pumping energy costs compared with the single-speed pump (SSP).