Skip to main navigation Skip to search Skip to main content

Uncertainty and state estimation in gas transmission networks

  • M. A. Murray*
  • , H. P. Hong
  • , M. A. Nessim
  • , W. M. Grasdal
  • *Corresponding author for this work
  • Nova Corp

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The mathematical modelling of any physical system is prone to errors, the most common of which are the simplifying assumptions often needed to obtain a solution. Other potential sources of error are, inaccuracies in the input data and the treatment of some system parameters as being single valued when in fact they have random variability. All of these types of error are discussed in the paper in the context of a steady state gas transmission network model. A means of quantifying error propagation across a network is developed and illustrated by a worked example. The effect of introducing measured data into the mathematical model is also addressed with attention being paid to both measurement error and redundancy in the system of equations used to solve the network. The ensuing approach is both robust and simple to use on networks of any size and complexity.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE
PublisherPubl by ASME
Pages371-384
Number of pages14
ISBN (Print)0791807878
StatePublished - 1993
Externally publishedYes
EventProceedings of the 12th International Conference on Offshore Mechanical and Arctic Engineering (OMAE 1993) - Glasgow, Scotland, Engl
Duration: 20 Jun 199324 Jun 1993

Publication series

NameProceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE
Volume5

Conference

ConferenceProceedings of the 12th International Conference on Offshore Mechanical and Arctic Engineering (OMAE 1993)
CityGlasgow, Scotland, Engl
Period20/06/9324/06/93

Fingerprint

Dive into the research topics of 'Uncertainty and state estimation in gas transmission networks'. Together they form a unique fingerprint.

Cite this