Optimizing the operation of the Haifa-A water-distribution network

Elad Salomons, Alexander Goryashko, Uri Shamir, Zhengfu Rao, Stefano Alvisi

Research output: Contribution to journalArticlepeer-review

Abstract

Haifa-A is the first of two case studies relating to the POWADIMA research project. It comprises about 20% of the city's water-distribution network and serves a population of some 60,000 from two sources. The hydraulic simulation model of the network has 126 pipes, 112 nodes, 9 storage tanks, 1 operating valve and 17 pumps in 5 discrete pumping stations. The complex energy tariff structure changes with hours of the day and days of the year. For a dynamically rolling operational horizon of 24 h ahead, the real-time, near-optimal control strategy is calculated by a software package that combines a genetic algorithm (GA) optimizer with an artificial neural network (ANN) predictor, the latter having replaced a conventional hydraulic simulation model to achieve the computational efficiency required for real-time use. This paper describes the Haifa-A hydraulic network, the ANN predictor, the GA optimizer and the demand- forecasting model that were used. Thereafter, it presents and analyses the results obtained for a full (simulated) year of operation in which an energy cost saving of some 25% was achieved in comparison to the corresponding cost of current practice. Conclusions are drawn regarding the achievement of aims and future prospects.

Original languageEnglish
Pages (from-to)51-64
Number of pages14
JournalJournal of Hydroinformatics
Volume9
Issue number1
DOIs
StatePublished - Jan 2007
Externally publishedYes

Keywords

  • Artificial neural network
  • Genetic algorithm
  • Optimal-control
  • POWADIMA
  • Water distribution

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Water Science and Technology
  • Geotechnical Engineering and Engineering Geology
  • Atmospheric Science

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