Daily Urban Water Consumption Prediction and Optimization of Pumping Station Operation Hours: A Case Study of Najafabad

Articles in Press

Authors

1 Civil and transportation faculty, Isfahan University, Isfahan, Iran

2 Prof., Isfahan University of Tech.

3 Water and Wastewater Company of Isfahan Province

4 Water and Wastewater Of Isfahan Province

Abstract

In recent years, engineers and operators have shown a greater interest in employing optimization method and making networks smart over other costlier and time-consuming approaches such as network rehabilitation, asset management, and network equipment upgrading. In the present study, the daily water consumption in the urban water distribution network is predicted based on four input features: day of the year, day of the week, continuity of holidays, and maximum daily air temperature, using moving average methods, linear regression, some artificial intelligence methods including multilayer perceptron neural network, and radial basis function neural network. Subsequently, based on the predicted values, the optimal scheduling of pump station activation hours is determined considering the hourly consumption pattern and the water levels in the upstream and downstream reservoirs of the pumping station. This scheduling aims to reduce the electricity cost of the pumping station with the fixed speed pumps based on different electricity tariffs. The method has been applied to the Najafabad urban water network, resulting in a reduction of 1.2% to 13.3% in the electricity cost of the pumping station compared to the traditional operational mode due to the different time interval parameter values for pumping.

Keywords

Journal of Water and Wastewater Science and Engineering

Articles in Press, Accepted Manuscript
Available Online from 22 January 2024

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History

  • Receive Date: 13 August 2023
  • Revise Date: 16 January 2024
  • Accept Date: 22 January 2024

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