Optimal Pump Scheduling for Urban Drainage under Variable Flow Conditions

Oreste Fecarotta, Armando Carravetta, Maria Cristina Morani and Roberta Padulano
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Oreste Fecarotta: Department of Civil, Architectural and Environmental Engineering, University of Naples “Federico II”, 80125 Naples, Italy
Armando Carravetta: Department of Civil, Architectural and Environmental Engineering, University of Naples “Federico II”, 80125 Naples, Italy
Maria Cristina Morani: Department of Civil, Architectural and Environmental Engineering, University of Naples “Federico II”, 80125 Naples, Italy
Roberta Padulano: Regional Models and Geo-Hydrological Impacts (REMHI), CMCC Foundation (Euro Mediterranean Center on Climate Change), Via Maiorise, 81043 Capua, Italy

Resources, 2018, vol. 7, issue 4, 1-20

Abstract: The paper is focused on the optimal scheduling of a drainage pumping station, complying with variations in the pump rotational speed and a recurrent pattern for the inflow discharge. The paper is structured in several consecutive steps. In the first step, the experimental set-up is described and results of calibration tests on different pumping machines are presented to obtain equations linking significant variables (discharge, head, power, efficiency). Then, those equations are utilized to build a mixed-integer optimization model able to find the scheduling solution that minimizes required pumping energy. The model is solved with respect to a case study referred to a urban drainage system in Naples (Italy) and optimization results are analysed to provide insights on the algorithm computational performance and on the influence of pumping machine characteristics on the overall efficiency savings. With reference to the simulated scenarios, an average value of 32% energy can be saved with an optimized control. Its actual value depends on the hydraulic characteristics of the system.

Keywords: pump scheduling; energy management in water systems; energy saving in water systems; urban drainage; sewage pump; wet well; pumping station (search for similar items in EconPapers)
JEL-codes: Q1 Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2018
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