In water distribution systems, pumps are used for supplying water from low points to elevated tanks that supply the network’s demands. The pumps are operated in different ways that could be distinguished by the complexity of the required control system. Such control systems range from pressure and time-based controls, through simple fixed ON-OFF trigger levels (e.g., a bang-bang controller) to complex online pump optimization schemes based on water demand predictions [e.g., the model predictive controller (MPC)]. In this study, we propose an off-line optimization method that utilizes dynamic trigger levels for pump operations. More specifically, these trigger dynamics are optimized according to electricity tariff structure, pump operation conditions, and long demand series in order to allow a more robust operation. We also provide a multiobjective analysis for the optimization problem and analyze the impact of different objectives on the obtained solution. In addition, the methodology is also demonstrated on real-world data.
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Housh et al. (2018) studied this question.
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