Stochastic Approach for Optimal Positioning of Pumps As Turbines (PATs)

Mariacrocetta Sambito, Stefania Piazza and Gabriele Freni
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Mariacrocetta Sambito: Department of Engineering, University of Palermo, Viale delle Scienze, Ed. 8, 90100 Palermo, Italy
Stefania Piazza: School of Engineering and Architecture, University of Enna “Kore”, 94100 Enna, Italy
Gabriele Freni: School of Engineering and Architecture, University of Enna “Kore”, 94100 Enna, Italy

Sustainability, 2021, vol. 13, issue 21, 1-12

Abstract: A generic water system consists of a series of works that allow the collection, conveyance, storage and finally the distribution of water in quantities and qualities such as to satisfy the needs of end users. In places characterized by high altitude differences between the intake works and inhabited centres, the potential energy of the water is very high. This energy is attributable to high pressures, which could compromise the functionality of the pipelines; it is therefore necessary to dissipate part of this energy. A common alternative to dissipation is the possibility of exploiting this energy by inserting a hydraulic turbine. The present study aims to evaluate the results obtained from a stochastic approach for the solution of the multi-objective optimization problem of PATs (Pumps As Turbines) in water systems. To this end, the Bayesian Monte Carlo optimisation method was chosen for the optimization of three objective functions relating to pressure, energy produced and plant costs. The case study chosen is the Net 3 literature network available in the EPANET software manual. The same problem was addressed using the NSGA-III (Nondominated Sorting Genetic Algorithm) to allow comparison of the results, since the latter is more commonly used. The two methods have different peculiarities and therefore perform better in different contexts.

Keywords: pump as turbine; energy recovery; water distribution system; Bayesian Monte Carlo method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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