  Optimizing pump operations is a challenging task for real-time management of
water distribution systems (WDSs). With suitable pump scheduling, pumping costs
can be significantly reduced. In this research, a novel economic model
predictive control (EMPC) framework for real-time management of WDSs is
proposed. Optimal pump operations are selected based on predicted system
behavior over a receding time horizon with the aim to minimize the total
pumping energy cost. Time-varying electricity tariffs are considered while all
the required water demands are satisfied. The novelty of this framework is to
choose the number of pumps to operate in each pump station as decision
variables in order to optimize the total pumping energy costs. By using integer
programming, the proposed EMPC is applied to a benchmark case study, the
Richmond Pruned network. The simulation with an EPANET hydraulic simulator is
implemented. Moreover, a comparison of the results obtained using the proposed
EMPC with those obtained using trigger-level control demonstrates significant
economic benefits of the proposed EMPC.
