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Quantitative evaluation of availability measures of gas distribution networks

Published: 10 December 2013 Publication History

Abstract

Rising competition among gas distribution companies, growing availability of smart metering devices, and increasingly strict requirements on agreed service levels stimulate research on advanced modeling and solution techniques for quantitative evaluation of gas distribution networks. We propose a novel methodology for modeling and evaluation of the transient network behavior after a component failure.
The approach relies on a topological model of the fluid dynamics and a stochastic timed model of the actions started after a component failure. Fluid dynamic analysis evaluates the service level of end-users in each possible operating condition of the network, also supporting the derivation of stochastic parameters for the failure management model. In turn, such model is analyzed to evaluate the probability over time of the network operating conditions. Transient probabilities are then aggregated on the basis of the results of fluid dynamic analysis to derive availability measures. Special attention is paid to make the structure of the stochastic model independent of the network topology. To provide a proof of concept, the approach is exemplified on a small-sized network equipped with a backup pipe, evaluating for each end-user the transient probability of not being served after a component failure as well as the mean outage time. These measures comprise a valid ground for the evaluation of different failure management processes and the definition of demand-response strategies.

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  • (2017)An introduction to the ORIS toolProceedings of the 11th EAI International Conference on Performance Evaluation Methodologies and Tools10.1145/3150928.3158361(9-11)Online publication date: 5-Dec-2017

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cover image ACM Other conferences
ValueTools '13: Proceedings of the 7th International Conference on Performance Evaluation Methodologies and Tools
December 2013
336 pages
ISBN:9781936968480

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  • EAI: The European Alliance for Innovation
  • ICST

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ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)

Brussels, Belgium

Publication History

Published: 10 December 2013

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Author Tags

  1. Markov regenerative processes
  2. gas distribution networks
  3. stochastic state classes
  4. transient availability measures

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  • (2017)An introduction to the ORIS toolProceedings of the 11th EAI International Conference on Performance Evaluation Methodologies and Tools10.1145/3150928.3158361(9-11)Online publication date: 5-Dec-2017

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