Minimizing Pumping Energy Cost in Real-Time Operations of Water Distribution Systems Using Economic Model Predictive Control
Publication: Journal of Water Resources Planning and Management
Volume 147, Issue 7
Abstract
Optimizing pump operations is a challenging task for real-time management of water distribution systems (WDS). 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 WDS 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.
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Data Availability Statement
Some data, models, or code generated or used during the study are available in the following online repository in accordance with funder data retention policies: https://github.com/yewangunimelb/watersystem.
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Published In
Journal of Water Resources Planning and Management
Volume 147 • Issue 7 • July 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Sep 1, 2020
Accepted: Jan 28, 2021
Published online: May 13, 2021
Published in print: Jul 1, 2021
Discussion open until: Oct 13, 2021
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