Modelling maximum daily gas flow on exits of gas transmission networks using mixtures

We present an approach for modelling heterogeneous gas flow patterns in gas transmission networks based on mixtures of generalized nonlinear models (GNMs). This enables the use of a gamma distribution for the dependent variable and to incorporate standard loading profile specifications based on nonlinear functions where the specific form to be used is explicitly prescribed by a regulatory framework agreement. We focus in particular on the modelling of the maximum daily gas flow to predict gas flow at low temperatures where we take into account if the weekday is a working day or a non-working day. The application to a gas flow dataset from Western Austria exemplifies the benefits of using mixture models to obtain maximum gas flow predictions while taking day characteristics into account.

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Publication Details

Journal
Statistical Modelling
Published
2025-11-14
DOI
https://doi.org/10.1177/1471082x251379265
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Modelling maximum daily gas flow on exits of gas transmission networks using mixtures

Bettina Grün, Sanela Omerovic, Herwig Friedl
Statistical Modelling
Integrated Energy Systems Optimization
article

Modelling maximum daily gas flow on exits of gas transmission networks using mixtures

Bettina Grün, Sanela Omerovic, Herwig Friedl
article en

Abstract

We present an approach for modelling heterogeneous gas flow patterns in gas transmission networks based on mixtures of generalized nonlinear models (GNMs). This enables the use of a gamma distribution for the dependent variable and to incorporate standard loading profile specifications based on nonlinear functions where the specific form to be used is explicitly prescribed by a regulatory framework agreement. We focus in particular on the modelling of the maximum daily gas flow to predict gas flow at low temperatures where we take into account if the weekday is a working day or a non-working day. The application to a gas flow dataset from Western Austria exemplifies the benefits of using mixture models to obtain maximum gas flow predictions while taking day characteristics into account.

Statistical Modelling
Vienna University of Economics and Business (AT), Graz University of Technology (AT)
Openalex Percentile: Top 66%
Integrated Energy Systems Optimization
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