Convex relaxations for gas expansion planning

Borraz-Sanchez, Conrado; Bent, Russell Whitford; Backhaus, Scott N.; Hijazi, Hassan; Van Hentenryck, Pascal

doi:10.1287/ijoc.2016.0697

Convex relaxations for gas expansion planning

Journal Article · Thu Dec 31 23:00:00 EST 2015 · INFORMS Journal on Computing

DOI:https://doi.org/10.1287/ijoc.2016.0697· OSTI ID:1296664

Borraz-Sanchez, Conrado ^[1]; Bent, Russell Whitford ^[1]; Backhaus, Scott N. ^[1]; Hijazi, Hassan ^[2]; Van Hentenryck, Pascal ^[2]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
NICTA and ANU, Canberra (Australia)

Expansion of natural gas networks is a critical process involving substantial capital expenditures with complex decision-support requirements. Here, given the non-convex nature of gas transmission constraints, global optimality and infeasibility guarantees can only be offered by global optimisation approaches. Unfortunately, state-of-the-art global optimisation solvers are unable to scale up to real-world size instances. In this study, we present a convex mixed-integer second-order cone relaxation for the gas expansion planning problem under steady-state conditions. The underlying model offers tight lower bounds with high computational efficiency. In addition, the optimal solution of the relaxation can often be used to derive high-quality solutions to the original problem, leading to provably tight optimality gaps and, in some cases, global optimal solutions. The convex relaxation is based on a few key ideas, including the introduction of flux direction variables, exact McCormick relaxations, on/off constraints, and integer cuts. Numerical experiments are conducted on the traditional Belgian gas network, as well as other real larger networks. The results demonstrate both the accuracy and computational speed of the relaxation and its ability to produce high-quality solution

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1296664

Report Number(s):: LA-UR-15-24636

Journal Information:: INFORMS Journal on Computing, Journal Name: INFORMS Journal on Computing Journal Issue: 4 Vol. 28; ISSN 1091-9856

Publisher:: INFORMSCopyright Statement

Country of Publication:: United States

Language:: English

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GasLib—A Library of Gas Network Instances Schmidt, Martin; Aßmann, Denis; Burlacu, Robert Data, Vol. 2, Issue 4 https://doi.org/10.3390/data2040040	journal	December 2017

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