Optimization and Engineering

, Volume 8, Issue 3, pp 259–275 | Cite as

Deterministic global optimization approach to steady-state distribution gas pipeline networks



Natural gas is normally transported through a vast network of pipelines. A pipeline network is generally established either to transmit gas at high pressure from coastal supplies to regional demand points (transmission network) or to distribute gas to consumers at low pressure from the regional demand points (distribution network). In this study, the distribution network is considered. The distribution network differs from the transmission one in a number of ways. Pipes involved in a distribution network are often much smaller and the network is simpler, having no valves, compressors or nozzles. In this paper, we propose the problem of minimizing the cost of pipelines incurred by driving the gas in a distribute non-linear network under steady-state assumptions. In particular, the decision variables include the length of the pipes’ diameter, pressure drops at each node of the network, and mass flow rate at each pipeline leg. We establish a mathematical optimization model of this problem, and then present a global approach, which is based on the GOP primal-relaxed dual decomposition method presented by Visweswaran and Floudas (Global optimization in engineering design. Kluwer book series in nonconvex optimization and its applications. Kluwer, Netherlands, 1996), to the optimization model. Finally, results from application of the approach to data from gas company are presented.


Distribution network Gas pipeline network Nonlinear network optimization Steady-state 


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.School of ManagementUniversity of Southampton HighfieldSouthamptonUK
  2. 2.Department of Management SciencesCity University of Hong KongHong KongHong Kong
  3. 3.College of Business AdministrationHunan UniversityHunanChina
  4. 4.Department of Applied MathematicsDalian University of TechnologyDalianChina

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