Tight MILP formulation for pipeline gas flow with linepack

In integrated power and gas energy system optimization models (ESOMs), pipeline gas transmission with linepack is a particularly complex problem due to its non-linear and non-convex character. For ESOMs based on mixed-integer linear programming, piecewise linearization is a well-established convexification approach for this problem, which, however, requires binary variables to model feasible combinations of linear gas flow and pressure segments and thus can quickly become computationally challenging. In order to improve computational performance, this paper proposes a piecewise linearization method specifically designed to be tight, resulting in a reduced problem space a solver can explore faster. We provide numerical results comparing the proposed formulation against two piecewise linearizations from the literature, both from a theoretical point of view and in terms of practical computational performance, with results showing an average speed-up of 2.57 times for our case study. Test cases are carried out on a modified 24-bus IEEE Reliability Test System and a 12-node gas system, considering discrete unit commitment decisions. • Tight piecewise linearization method for pipeline gas transmission with linepack. • Computational speed-up due to tightness and reduced number of variables. • Reduced number of vertices in polyhedron implies reduced linear program complexity. • Case study of integrated power and gas energy system optimization model.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2025-05-25
DOI
https://doi.org/10.1016/j.ijepes.2025.110734
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73
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article

Tight MILP formulation for pipeline gas flow with linepack

Germán Morales-España, Diego A. Tejada‐Arango, Thomas Klatzer, Sonja Wogrin
1 citations
International Journal of Electrical Power & Energy Systems
Integrated Energy Systems Optimization
0.73
article

Tight MILP formulation for pipeline gas flow with linepack

Germán Morales-España, Diego A. Tejada‐Arango, Thomas Klatzer, Sonja Wogrin
article en
1 citations

Abstract

In integrated power and gas energy system optimization models (ESOMs), pipeline gas transmission with linepack is a particularly complex problem due to its non-linear and non-convex character. For ESOMs based on mixed-integer linear programming, piecewise linearization is a well-established convexification approach for this problem, which, however, requires binary variables to model feasible combinations of linear gas flow and pressure segments and thus can quickly become computationally challenging. In order to improve computational performance, this paper proposes a piecewise linearization method specifically designed to be tight, resulting in a reduced problem space a solver can explore faster. We provide numerical results comparing the proposed formulation against two piecewise linearizations from the literature, both from a theoretical point of view and in terms of practical computational performance, with results showing an average speed-up of 2.57 times for our case study. Test cases are carried out on a modified 24-bus IEEE Reliability Test System and a 12-node gas system, considering discrete unit commitment decisions. • Tight piecewise linearization method for pipeline gas transmission with linepack. • Computational speed-up due to tightness and reduced number of variables. • Reduced number of vertices in polyhedron implies reduced linear program complexity. • Case study of integrated power and gas energy system optimization model.

International Journal of Electrical Power & Energy SystemsVol. 169
Energy Research Centre of the Netherlands (NL), Graz University of Technology (AT), Universidad Pontificia Comillas (ES), Delft University of Technology (NL)
Openalex Percentile: Top 28%
Integrated Energy Systems Optimization
0.73
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Tight MILP formulation for pipeline gas flow with linepack — Germán Morales-España, Diego A. Tejada‐Arango, et al. · International Journal of Electrical Power & Energy Systems (2025) | TGRS Research Map | TGRS