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Optimizing pump operations is a challenging task for real-time management ofwater distribution systems (WDSs). With suitable pump scheduling, pumping costscan be significantly reduced. In this research, a novel economic modelpredictive control (EMPC) framework for real-time management of WDSs isproposed. Optimal pump operations are selected based on predicted systembehavior over a receding time horizon with the aim to minimize the totalpumping energy cost. Time-varying electricity tariffs are considered while allthe required water demands are satisfied. The novelty of this framework is tochoose the number of pumps to operate in each pump station as decisionvariables in order to optimize the total pumping energy costs. By using integerprogramming, the proposed EMPC is applied to a benchmark case study, theRichmond Pruned network. The simulation with an EPANET hydraulic simulator isimplemented. Moreover, a comparison of the results obtained using the proposedEMPC with those obtained using trigger-level control demonstrates significanteconomic benefits of the proposed EMPC.

Minimizing Pumping Energy Cost in Real-time Operations of Water Distribution Systems using Economic Model Predictive Control