Least-cost design of water distribution systems under demand uncertainty: The robust counterpart approach

Lina Perelman, Mashor Housh, Avi Ostfeld

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, a non-probabilistic robust counterpart (RC) approach is demonstrated and applied to the least-cost design/rehabilitation problem of water distribution systems (WDSs). The uncertainty of the information is described by a deterministic user-defined ellipsoidal uncertainty set that implies the level of risk. The advantages of the RC approach on previous modelling attempts to include uncertainty are in making no assumptions about the probability density functions of the uncertain parameters and their interdependencies, having no requirements on the construction of a representative sample of scenarios, and the deterministic equivalent problem preserves the same size (i.e. computational complexity) as the original problem. The RC is coupled with the cross-entropy heuristic optimization technique for seeking robust solutions. The methodology is demonstrated on an illustrative example and on the Hanoi network. The results show considerable promise of the proposed approach to incorporate uncertainty in the least-cost design problem of WDSs. Further research is warranted to extend the model for more complex WDSs, incorporate extended period simulations, and develop RC schemes for other WDSs related management problems.

Original languageEnglish
Pages (from-to)737-750
Number of pages14
JournalJournal of Hydroinformatics
Volume15
Issue number3
DOIs
StatePublished - 2013
Externally publishedYes

Keywords

  • Least-cost design
  • Robust optimization
  • Uncertainty
  • Water distribution systems

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Least-cost design of water distribution systems under demand uncertainty: The robust counterpart approach'. Together they form a unique fingerprint.

Cite this