Pumping Station Design with an Analysis of Variability of Demand and Considering Techno-Economic and Environmental Criteria through the AHP Method

Abstract

[EN] Pumping stations costs including, capital and operational costs are some of the highest costs in urban water distribution system. A proper pumping station design could be defined as the solution with the minimum life cycle cost and satisfying extreme scenarios in water distribution system. These costs are associated with investment, operational and maintenance costs. However, there are some important aspects to consider un a pumping station design, such as the feasibility of infrastructure construction, the size of the infrastructure, and the complexity of operation in the pumping station. These aspects are associated with technical criteria. In a classical pumping station design, the number of pumps is determined in arbitrary form according to the criteria of the engineer, and the pump model is selected according to the maximum requirements of flow and pressure of the network. In summary, these variables in a pumping station design are not usually analyzed deeply. In addition, global warming acceleration in the last decades has gained momentum to be considered in engineering problems to mitigate the environmental impact. Hence, it is imperative to consider environmental aspects, such as greenhouse emission, energetic efficiency of the pump in modern pumping systems of water distribution networks. Finally, the most suitable solution is determined only by analyzing economic aspects. Therefore, this work proposed a methodology to design pumping stations in urban water networks considering technical, environmental, and economic criteria and link them together through the Analytic Hierarchy Process (AHP) method. The propose of this method is to determine the importance priority of these aspects to assess the possible solutions and determine the most suitable solution in the pumping station design. In addition, this work considers the variability of demand pattern. This work analyses several scenarios of demand patterns from the minimum possible demand to the maximum possible demand in a water distribution network and the respective probabilities of occurrence of scenario. It allows that the pumping station design be more robust. This methodology has been applied in different case studies to analyze how affects to determine the most suitable solution when the characteristics of the network change.