Modeling bidirectional flows in gas networks.
Saved in:
| Title: | Modeling bidirectional flows in gas networks. |
|---|---|
| Authors: | Schinke-Nendza, Aiko1 (AUTHOR) aiko.schinke-nendza@uni-due.de, Conejo, Antonio J.2 (AUTHOR), Weber, Christoph1 (AUTHOR) |
| Source: | Optimization & Engineering. Jun2026, Vol. 27 Issue 2, p1355-1396. 42p. |
| Subjects: | Gas flow, Compressor performance, Convex programming, Renewable energy sources, Gas distribution, Energy infrastructure, Fluid flow |
| Abstract: | Achieving climate neutrality in Europe by 2050 requires a fundamental transformation of the energy system. As renewable integration accelerates, cross-sectoral technologies and green gases are gaining importance as flexible assets to support the electricity system. This transition increases the need for gas network models that are both computationally tractable and physically accurate—especially for large-scale, quasi-dynamic applications. This paper introduces two globally convex gas flow formulations based on polyhedral McCormick-type relaxations of the nonlinear Weymouth equation. Further, two compressor relaxations are introduced that retain the models' convex structure. These models capture the bidirectional flow dynamics of pipelines and the operating modes of compressors without relying on mixed-integer variables, enabling scalable optimization. A comprehensive benchmark against established flow models—including mixed-integer and linear approximations—demonstrates the proposed formulations' ability to balance fidelity and efficiency. The models are critically assessed in terms of approximation accuracy to the Weymouth equation and applied to a real-world case study of the German gas transmission network. Results show that the proposed relaxations achieve competitive accuracy compared to state-of-the-art mixed-integer models while significantly reducing computational burden. Their robustness, scalability, and physical consistency highlight their potential as a practical modeling tool for future gas and hydrogen infrastructure studies and integrated energy system planning. [ABSTRACT FROM AUTHOR] |
| Copyright of Optimization & Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!