Modelling maximum daily gas flow on exits of gas transmission networks using mixtures
Year: 2025
Type: article
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.
Source: Statistical Modelling
Authors: Sanela Omerovic, Herwig Friedl, Bettina Grün
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,650
OpenAlex ID: W4416230476