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Deterministic global optimisation approach to steady-state distribution gas pipeline networks (In special issue: Optimization and Control Applications)

Deterministic global optimisation approach to steady-state distribution gas pipeline networks (In special issue: Optimization and Control Applications)
Deterministic global optimisation approach to steady-state distribution gas pipeline networks (In special issue: Optimization and Control Applications)
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
1389-4420
259-275
Wu, Y.
e279101b-b392-45c4-b894-187e2ded6a5c
Lai, K.K.
20379c9f-ac5f-4549-ab91-77722180b971
Liu, Y.
621975c3-5440-4f2c-b313-4e724228220d
Wu, Y.
e279101b-b392-45c4-b894-187e2ded6a5c
Lai, K.K.
20379c9f-ac5f-4549-ab91-77722180b971
Liu, Y.
621975c3-5440-4f2c-b313-4e724228220d

Wu, Y., Lai, K.K. and Liu, Y. (2007) Deterministic global optimisation approach to steady-state distribution gas pipeline networks (In special issue: Optimization and Control Applications). Optimization and Engineering, 8 (3), 259-275. (doi:10.1007/s11081-007-9018-y).

Record type: Article

Abstract

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.

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More information

Published date: September 2007
Keywords: distribution network, gas pipeline network, nonlinear network optimization, steady-state

Identifiers

Local EPrints ID: 58635
URI: http://eprints.soton.ac.uk/id/eprint/58635
ISSN: 1389-4420
PURE UUID: c5614375-c622-4b6c-bdd9-959cf328aedb

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Date deposited: 15 Aug 2008
Last modified: 16 Mar 2024 03:39

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Contributors

Author: Y. Wu ORCID iD
Author: K.K. Lai
Author: Y. Liu

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