A Decision Support Tool for Minimizing Energy Consumption in Water Distribution Networks

  • Abdulla Sayedna Mohammed

    Student thesis: Master's Thesis

    Abstract

    Economic development and population growth are continuously increasing the pressure on water utilities. Water transmission and distribution is considered an energy-intensive process. The major energy consumption in water networks is due to pumping. Minimizing the energy consumption of the pumps has become the primary target for many water utilities around the world. This research aims to develop a decision tool to optimize pump operation costs for any pumping station. A pilot case study from TRANSCO water network is selected to develop the new optimization tool. The case study consists of two water pumping stations, six variable speed pumps, six tanks, and nine demand nodes. The operation system of these pumping stations automatically controls all the variables (motor speed, pressure, flowrate, valve opening, and closing) that will satisfy the hydraulic requirement of the water network. Currently, the start and stop of each pump are decided based on human experience regardless of the electricity tariff. In this study, a new optimization decision tool is developed to help the operation decide the optimum pumping flowrate for the upcoming 24 hours, minimizing pumping cost and satisfying all requirements and constraints. The model requires the user to fill the hourly demand forecast at each demand node, electricity tariff, initial tanks level, maximum and minimum pump flowrate. The optimization model uses a linear programming algorithm to find the optimum flowrate for 24 hours. AIMMS optimization software was selected for the implementation of the optimization model and the development of a user friendly interface. The optimum flowrates were tested on EPANET to verify the feasibility of the optimum schedule from hydraulics perspectives. Results show that the new optimization tool is robust and has successfully reduced the cost of the pumping station up to 9%.
    Date of AwardMay 2022
    Original languageAmerican English

    Keywords

    • Water Network
    • Optimization of Pumping Station
    • Water Distribution Optimization
    • Pumping Cost Optimization.

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