Technical Papers
May 18, 2015

Modeling, Simulation, and Optimization of a High-Pressure Cross-Country Natural Gas Pipeline: Application of an Ant Colony Optimization Technique

Publication: Journal of Pipeline Systems Engineering and Practice
Volume 7, Issue 1

Abstract

The process of natural gas transportation through cross-country pipelines, with intermittent repressurization with the help of compressors that use part of the same gas for energy source, is a very interesting optimization problem that has attracted researchers. In the present work, an 18-node network connecting a single source to a single delivery point has been selected for analysis. A steady-state model, incorporating gas flow dynamics, compressor characteristics, and mass balance equations, has been developed. Ant colony optimization, a comparatively new evolutionary technique in pipeline optimization, has been used for minimizing fuel consumption for a fixed throughput. A comparison with a similar optimization tool, a solver of a general algebraic modeling system that extracts the principle of generalized reduced gradient algorithm, indicates an improved solution in terms of fuel consumption minimization.

Get full access to this article

View all available purchase options and get full access to this article.

References

Adeyanju, O. A., and Oyekunle, L. O. (2004). “Optimization of natural gas transportation in pipelines.” Petroleum and Gas Engineering Program, Univ. of Logos, Nigeria.
Bakhouya, B., and Wolf, D. (2008). “Solving gas transmission problems by taking compressors into account.” HECEcole de Gestiondel’Université de Liege (ULG), Dunkerque, France.
Carter, R. G. (1996). “Compressor station optimization: Computational accuracy and speed.” 28th Annual Meeting of Pipeline Simulation Interest Group, Pennwell Publishing, OK.
Chebouba, A., Yalaoui, F., Amodeo, L., Smati, A., and Tairi, A. (2006). “A new method to minimize fuel consumption of gas pipeline using ant colony optimization algorithms.” Proc., 2006 Int. Conf. on Service Systems and Service Management, IEEE, New York.
Conrado, B. S., and Rozer, M. (2005). A hybrid meta-heuristic approach for natural gas pipeline network optimization, Springer, Berlin.
Diana, C. Z., and Rozer, M. (2002). “A MINLP model for a minimizing fuel consumption on natural gas pipeline networks.” Memoriasdel XI Congreso Latino Iberoamericano de Investigación de Operaciones(CLAIO), Springer.
Dorigo, M., and Stützle, T. (2004). Ant colony optimization, MIT Press, Cambridge, MA.
Dudley, B. (2013). “BP statistical reviews of world energy.” 〈〉.
Elbeltagi, E., Hegazy, T., and Grierson, D. (2005). “Comparison among five evolutionary based optimization algorithm.” Adv. Eng. Inform., 19(1), 43–53.
Ferber, E., Philip, P., William, B., and Ujjal, V. (1999). “CNGT installs fuel minimization system to reduce operating cost.” Pipeline and Gas Industry, 97–102.
Grelli, G. J. (1985). “Implementing an optimization program for a natural gas transmission pipeline.” Pipeline Simulation Interest Group, Albuquerque, New Mexico.
Jamshidifar, A., Torbati, H. M., and Kazemian, M. (2009). “GTNOpS, an agent-based optimization software for gas transmission network.” 24th World Gas Conf., Argentina.
MATLAB R 2010 version 7.10.0.499 [Computer software]. Natick, MA, Mathworks.
Menon, E. S. (2005). Gas pipeline hydraulics, CRC Press, Taylor and Francis Group, Boca Raton, FL.
Mohajeri, I., and Taffazzoli, R. (2012). “Optimization of tree-structured gas distribution network using ant colony optimization: A case study.” IJE Trans. A: Basics, 25(2), 141–156.
Mohring, J., Hoffmann, J., Halfmann, T., Zemitis, A., Basso, G., and Lagoni, P. (2004). “Automated model reduction of complex gas pipeline networks.” Proc., 36th Annual Meeting of Pipeline Simulation Interest Group, Palm Springs, CA.
Osiadacz, A. J. (1994). “Dynamic optimization of high pressure gas networks using hierarchical systems theory.” 26th annual meeting of Pipeline Simulation Interest Group, San Diego.
Ríos Mercado, R., Wu, S., Scott, L., and Boyd, E. (2002). “A reduction technique for natural gas transmission network optimization problems.” Ann. Oper. Res., 117(1), 217–234.
Rozer, M. (2003). “Efficient operation of natural gas pipeline networks.” Computational Finding of High Quality Solutions, Int. Applied Business Research Conf., AccessEcon.
Schlueter, M. (2012). “Nonlinear mixed integer based optimization technique for space application.” Ph.D. thesis, Univ. of Birmingham, England.
Smith, J., and Van Ness, H. (1998). Introduction to chemical engineering thermodynamics, 4th Ed., McGraw-Hill Book Company, Singapore.
Summing, W., Rios-Mercado, R. Z., Boyd, E. A., and Scott, L. R. (2000). “Model relaxation for the fuel minimization of steady state gas pipeline networks.” Math. Comput. Model., 31(2–3), 197–200.
Tabkhi, F. (2007). “Optimization of gas transmission networks.” Ph.D. thesis, Grenoble Institute of Technology (INP), Grenoble, France.
Uraikul, V., and Chan, C. W. (2004). “A mixed- integer optimization model for compressor selection in natural gas pipeline network system operations.” J. Environ. Inform., 3(1), 33–41.

Information & Authors

Information

Published In

Go to Journal of Pipeline Systems Engineering and Practice
Journal of Pipeline Systems Engineering and Practice
Volume 7Issue 1February 2016

History

Received: Oct 27, 2014
Accepted: Mar 11, 2015
Published online: May 18, 2015
Discussion open until: Oct 18, 2015
Published in print: Feb 1, 2016

Permissions

Request permissions for this article.

Authors

Affiliations

Adarsh Kumar Arya [email protected]
Assistant Professor, Dept. of Chemical Engineering, College of Engineering Studies, Univ. of Petroleum and Energy Studies, Energy Acres, Bidholi, Dehradun, Uttarakhand 248007, India (corresponding author). E-mail: [email protected]
Shrihari Honwad [email protected]
Senior Professor, Dept. of Chemical Engineering, College of Engineering Studies, Univ. of Petroleum and Energy Studies, Energy Acres, Bidholi, Dehradun, Uttarakhand 248007, India. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share