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The design of pumping stations in a water distribution network determines the investment costs and affects a large part of the operating costs of the network. In recent years, it was shown that it is possible to use flow distribution to optimize both costs concurrently; however, the methodologies proposed in the literature are not applicable to real-sized networks. In these cases, the space of solutions is huge, a small number of feasible solutions exists, and each evaluation of the objective function implies significant computational effort. To avoid this gap, a new method was proposed to reduce the search space in the problem of pumping station design. This method was based on network preprocessing to determine in advance the maximum and minimum flow that each pump station could provide. According to this purpose, the area of infeasibility is limited by ranges of the decision variable where it is impossible to meet the hydraulic constraints of the model. This area of infeasibility is removed from the search space with which the algorithm works. To demonstrate the benefits of using the new technique, a new real-sized case study was presented, and a pseudo-genetic algorithm (PGA) was implemented to resolve the optimization model. Finally, the results show great improvement in PGA performance, both in terms of the speed of convergence and quality of the solution. [ABSTRACT FROM AUTHOR]

The optimal function of a water distribution network is reached when the consumer demands are satisfied using the lowest quantity of energy, maintaining the minimal pressure required at the same time. One way to achieve this is through optimization of flow rate injection based on the use of the setpoint curve concept. In order to obtain that, a methodology is proposed. It allows for the assessment of the flow rate and pressure head that each pumping station has to provide for the proper functioning of the network while the minimum power consumption is kept. The methodology can be addressed in two ways: the discrete method and the continuous method. In the first method, a finite set of combinations is evaluated between pumping stations. In the continuous method, the search for the optimal solution is performed using optimization algorithms. In this paper, Hooke-Jeeves and Nelder-Mead algorithms are used. Both the hydraulics and the objective function used by the optimization are solved through EPANET and its Toolkit. Two case studies are evaluated, and the results of the application of the different methods are discussed. [ABSTRACT FROM AUTHOR]

Pumping station (PS) designs in water networks basically contemplate technical and economic aspects. Technical aspects could be related to the number of pumps in PS and the operational modes of PS. Meanwhile, economic aspects could be related to all the costs that intervene in a PS design, such as investment, operational and maintenance costs. In general, water network designs are usually focused on optimizing operational costs or investment costs, However, some subjective technical aspects have not been approached, such as determining the most suitable pump model, the most suitable number of pumps and the complexity of control system operation in a PS design. Therefore, the present work aims to select the most suitable pump model and determine the priorities that technical and economic factors could have in a PS design by a multi-criteria analysis, such as an analytic hierarchy process (AHP). The proposed work will contemplate two main criteria, and every criterion will be integrated by sub-criteria to design a PS. In this way, technical factors (number of pumps and complexity of the operating system) and economic factors (investment, operational and maintenance costs) will be considered for a PS design. The proposed methodology consists of realizing surveys to a different group of experts that determines the importance of one criterion over each other criterion in a PS design through pairwise comparisons. Finally, this methodology will provide importance weight for the criteria and sub-criteria on the PS. Besides, this work will perform a rating of the considered alternatives of pump models in every case study, evaluating quantitatively every alternative with every criterion in the PS design. The main objective of this work will select the most adequate pump model according to the obtained rating, considering technical and economic aspects in every case study. [ABSTRACT FROM AUTHOR]

The control system's point is to bring the pumping curve close to the set-point curve. That concept is essential for proper design of a pumping station. An adequate design is focused not only on selecting the total number of pumps and the type of control to use (flow or pressure), but it also is important to determine the optimal number of fixed speed pumps (FSPs) and variable speed pumps (VSPs) for each flow rate. This work discusses the most common methods and procedures for control systems on a design of pumping stations with a proposed methodology. This methodology consists of expressing the characteristics of the pumping curve and the set-point curve in a dimensionless form so that the methodology is standardized for any pump model and set-point curve. These formulations allow us to discuss how the characteristic of a pump and the set-point curve of the network influence the optimal number of FSPs and VSPs in energy terms. In general, the objective of this work is to determine the most suitable total number of pumps in a pumping station design and to determine the optimal pumping configuration in every flow rate, thus the consumed energy would be the minimum. Additionally, this methodology develops an expression to estimate the performance of a frequency inverter when a VSP operates at different rotational speeds. This work will be applied to different study cases, and the obtained results allow us to question several usual procedures for pumping control system. In general, it can be concluded that the number of pumps of a pumping system cannot be inferred in a simple form without a deep analysis of a control system. [ABSTRACT FROM AUTHOR]