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Petroleum Science

, Volume 9, Issue 1, pp 89–92 | Cite as

Power optimization of gas pipelines via an improved particle swarm optimization algorithm

  • Zhiwei Zheng
  • Changchun WuEmail author
Article

Abstract

In past decades dynamic programming, genetic algorithms, ant colony optimization algorithms and some gradient algorithms have been applied to power optimization of gas pipelines. In this paper a power optimization model for gas pipelines is developed and an improved particle swarm optimization algorithm is applied. Based on the testing of the parameters involved in the algorithm which need to be defined artificially, the values of these parameters have been recommended which can make the algorithm reach efficiently the approximate optimum solution with required accuracy. Some examples have shown that the relative error of the particle swarm optimization over ant colony optimization and dynamic programming is less than 1% and the computation time is much less than that of ant colony optimization and dynamic programming.

Key words

Gas pipeline operation optimization particle swarm optimization algorithm 

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Copyright information

© China University of Petroleum (Beijing) and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Beijing Key Laboratory of Urban Oil and Gas Distribution TechnologyChina University of PetroleumBeijingChina

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