Gas composition tracking in transient pipeline flow

Abstract Tracking changes in gas composition in natural gas pipeline transport systems is becoming increasingly important to pipeline operators, since gas suppliers are shifting from long-term delivery contracts to shorter-term contracts, increasing delivery of gases from unconventional sources, and proposing to inject hydrogen and biomethane into the natural gas networks. The present study investigates two methods for tracking gas composition, one using a moving grid method, and one solving the advection equation using an implicit backward difference method. The methods were applied to a model of an onshore pipeline in the Polish transmission system, and a model of an offshore pipeline in the Norwegian transmission system. The differences between the measured and modeled compositions and transport times were investigated. Both methods reproduced the measured compositions and transport times well, with an error in total transport times of less than 2.0%. The implicit method was found to lose some of the finer details of the gas composition profiles due to numerical diffusion, while the moving grid method preserved the composition profiles.

[1]  Tom van der Hoeven Math in gas and the art of linearization , 2004 .

[2]  Andrzej J. Osiadacz,et al.  Verification of Transient Gas Flow Simulation Model , 2010 .

[3]  T. Hoeven Gas Quality Control In Simulation , 1998 .

[4]  M. Chaczykowski,et al.  Sensitivity of pipeline gas flow model to the selection of the equation of state , 2009 .

[5]  Antonie Oosterkamp,et al.  Pipeline Modeling – Impact of Ambient Temperature and Heat Transfer Modeling , 2015 .

[6]  P. Hendriks,et al.  Improved Capacity Utilization By Integrating Real-time Sea Bottom Temperature Data , 2006 .

[7]  Tatsuhiko Kiuchi,et al.  An implicit method for transient gas flows in pipe networks , 1994 .

[8]  M. Chaczykowski,et al.  Simulation of natural gas quality distribution for pipeline systems , 2017 .

[9]  M. Chaczykowski,et al.  Transient flow in natural gas pipeline – The effect of pipeline thermal model , 2010 .

[10]  Stefano Campanari,et al.  Dynamic modeling of natural gas quality within transport pipelines in presence of hydrogen injections , 2017 .

[11]  Jan Fredrik Helgaker,et al.  Validation of 1D flow model for high pressure offshore natural gas pipelines , 2014 .

[12]  Andrea Lanzini,et al.  Greening the gas network - The need for modelling the distributed injection of alternative fuels , 2017 .

[13]  Jerry L. Modisette Lagrange - A Pipeline Flow Model Based On Points Moving With the Fluid , 2004 .

[14]  Joachim Schenk,et al.  A new method for gas quality tracking in distribution grids , 2012 .

[15]  Bo Yu,et al.  Comparison study on the accuracy and efficiency of the four forms of hydraulic equation of a natural gas pipeline based on linearized solution , 2015 .

[16]  H. Daneshyar,et al.  One-dimensional compressible flow , 1976 .

[17]  Alexandre J. Chorin,et al.  Random choice solution of hyperbolic systems , 1976 .

[18]  F. White Viscous Fluid Flow , 1974 .

[19]  Michael J. Ryan,et al.  Methods For Performing Composition Tracking For Pipeline Networks , 1986 .

[20]  Jan Fredrik Helgaker,et al.  Modelling of Natural Gas Pipe Flow with Rapid Transients-case Study of Effect of Ambient Model☆ , 2015 .

[21]  C F Colebrook,et al.  TURBULENT FLOW IN PIPES, WITH PARTICULAR REFERENCE TO THE TRANSITION REGION BETWEEN THE SMOOTH AND ROUGH PIPE LAWS. , 1939 .

[22]  Sigmund Clausen,et al.  Improving Pipeline Flow Modeling by Multivariate Analysis , 2016 .

[23]  Jianzhong Wu,et al.  Steady state analysis of gas networks with distributed injection of alternative gas , 2016 .

[24]  Jan Fredrik Helgaker,et al.  Modeling Transient Flow in Long Distance Offshore Natural Gas Pipelines , 2013 .