Design of Pumping Stations Using a Multicriteria Analysis and the Application of the AHP Method

The pumping station is a very important hydraulic system in urban water supplies because the pumps raise the water head, ensuring the minimum pressure required in drinking water systems. In the design of a pumping station, one of the most important criteria is the number of pumps. However, in the traditional design, this criterion is defined arbitrarily. The other criteria are defined from the number of pumps and can produce a design that is not optimal. In addition, the traditional design does not consider the importance of the environment in choosing the pumps. The objective of this paper is to define a new design methodology for pumping stations. It has been developed using a multicriteria analysis in which nine criteria are evaluated. The application of the analytic hierarchy process (AHP) allows for finding an optimal solution. These design criteria have been associated in three cluster factors: technical factors; environmental factors; and economic factors. The results obtained allow us not only to validate the methodology but also to offer a solution to the problem of determining the most suitable model and the number of pumps for a pumping station.

[1]  C. Du Dynamic Evaluation of Sustainable Water Resource Systems in Metropolitan Areas: A Case Study of the Beijing Megacity , 2020, Water.

[2]  Larry W. Mays,et al.  Optimal Operation of Water Distribution Pumps Considering Water Quality , 2000 .

[3]  M. López-Ibáñez,et al.  Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks , 2008 .

[4]  M. F K Pasha,et al.  Optimal Pump Scheduling by Linear Programming , 2009 .

[5]  G. Coyle,et al.  Analytic Hierarchy Process ( AHP ) , 2004 .

[6]  Gyewoon Choi,et al.  Energy Cost Optimization for Water Distribution Networks Using Demand Pattern and Storage Facilities , 2018 .

[7]  F. Martínez-Solano,et al.  A Methodology for the Optimization of Flow Rate Injection to Looped Water Distribution Networks through Multiple Pumping Stations , 2016 .

[8]  G. Yu,et al.  Optimized pump scheduling in water distribution systems , 1994 .

[9]  Wenyan Wu,et al.  Enhancing the Reliability and Security of Urban Water Infrastructures through Intelligent Monitoring, Assessment, and Optimization , 2010 .

[10]  J. Nault,et al.  Lifecycle Assessment of a Water Distribution System Pump , 2015 .

[11]  Zoran Kapelan,et al.  Fast Hybrid Optimization Method for Effective Pump Scheduling , 2013 .

[12]  Ralf H. Kaspar,et al.  Group Aggregation Techniques for Analytic Hierarchy Process and Analytic Network Process: A Comparative Analysis , 2016 .

[13]  Josep Arnal,et al.  Parallel Programming Techniques Applied to Water Pump Scheduling Problems , 2014 .

[14]  Ana Iglesias,et al.  Optimization of the Design of Water Distribution Systems for Variable Pumping Flow Rates , 2020, Water.

[15]  Greg Rybarczyk,et al.  A multi-Criteria Wetland Suitability Index for Restoration across Ontario’s Mixedwood Plains , 2020, Sustainability.

[16]  A. Kurbatova,et al.  Using Multi-Criteria Decision Analysis to Select Waste to Energy Technology for a Mega City: The Case of Moscow , 2020, Sustainability.

[17]  Pedro L. Iglesias-Rey,et al.  Use of Fixed and Variable Speed Pumps in Water Distribution Networks with Different Control Strategies , 2021, Water.

[18]  Jiramate Changklom,et al.  Theoretical Estimation of Energy Balance Components in Water Networks for Top-Down Approach , 2021, Water.

[19]  Armando Carravetta,et al.  Zero-net energy management for the monitoring and control of dynamically-partitioned smart water systems , 2020 .

[20]  Thomas L. Saaty,et al.  Rank from comparisons and from ratings in the analytic hierarchy/network processes , 2006, Eur. J. Oper. Res..

[21]  T. Pelli,et al.  Energy indicators and savings in water supply , 2000 .

[22]  Thomas L. Saaty,et al.  DECISION MAKING WITH THE ANALYTIC HIERARCHY PROCESS , 2008 .

[23]  Aviad Shapira,et al.  AHP-Based Equipment Selection Model for Construction Projects , 2005 .