Optimal operation of multiquality water distribution systems: Unsteady conditions

Avi Ostfeld, Elad Salomons

Research output: Contribution to journalArticlepeer-review

Abstract

This paper describes the methodology and application of a genetic algorithm scheme tailor-made to EPANET, for optimizing the operation of a water distribution system under unsteady water quality conditions. The water distribution system consists of sources of different qualities, treatment facilities, tanks, pipes, control valves, and pumping stations. The objective is to minimize the total cost of pumping and treating the water for a selected operational time horizon, while delivering the consumers the required quantities at acceptable qualities and pressures. The decision variables for each of the time steps that encompass the total operational time horizon include: the scheduling of the pumping units, settings of the control valves, and treatment removal ratios at the treatment facilities. The constraints are: head and concentrations at the consumer nodes, maximum removal ratios at the treatment facilities, maximum allowable amounts of water withdrawals at the sources, and returning at the end of the operational time horizon to a prescribed total volume in the tanks. The model is explored through two example applications.

Original languageEnglish
Pages (from-to)337-359
Number of pages23
JournalEngineering Optimization
Volume36
Issue number3
DOIs
StatePublished - Jun 2004
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by the Fund for the Promotion of Research at the Technion, and by the Technion Grand Water Research Institute (GWRI). The valuable comments provided by the anonymous reviewers, and by Professor Uri Shamir are gratefully acknowledged.

Keywords

  • EPANET
  • Genetic algorithms
  • Optimal operation
  • Optimization
  • QualNet, OptiGA
  • Water distribution systems
  • Water quality

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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