Cookies?
Library Header Image
LSE Research Online LSE Library Services

Development of a synthesis tool for gas-to-liquid complexes

Ellepola, Jerome, Thijssen, Nort, Grievink, Johan, Baak, Govert, Avhale, Abhijeet and van Schijndel, Jan (2012) Development of a synthesis tool for gas-to-liquid complexes. Computers and Chemical Engineering, 42. pp. 2-14. ISSN 0098-1354

Full text not available from this repository.
Identification Number: 10.1016/j.compchemeng.2011.12.005

Abstract

Optimal synthesis of a Gas-To-Liquid complex is complicated due to many degrees of freedom in a highly constrained design space. One can choose between alternative, competing syngas manufacturing technologies, different types of Fischer–Tropsch catalysts and reactors, with numerous connectivity options and a range of operational conditions. On the other hand, the design space is confined by equipment, operational and knowledge constraints. Furthermore, economic performance needs to be aligned with carbon and energy efficiencies. To support GTL process design a computational synthesis tool is under development. Its purpose is to find and analyse the optimum structure and operational conditions for a given market scenario. The process model covers alternative syngas generation units and Fischer–Tropsch reactors with an extensive syngas recycle structure. The process units interact with the utility system, where power can be generated from off-gas and/or excess steam. The units are modelled in a reduced, input–output way by algebraic equations, reflecting mass and energy balances and pressure effects. A superstructure arises when considering multiple stages for Fischer–Tropsch synthesis with parallel reactors. The synthesis tool, implemented in AIMMS®, is applied to a realistic sample problem, showing profit optimisation by varying the distribution of NG to syngas generation units with different efficiencies. A sensitivity analysis is carried out by means of Singular Value Decomposition of sensitivity matrices to find dominant patterns of parametric influence on the optimum.

Item Type: Article
Official URL: http://www.sciencedirect.com/science/journal/00981...
Additional Information: © 2012 Elsevier
Divisions: Centre for Analysis of Time Series
Subjects: Q Science > Q Science (General)
Sets: Research centres and groups > Centre for the Analysis of Time Series (CATS)
Date Deposited: 25 Feb 2014 13:52
Last Modified: 30 Jan 2019 18:58
URI: http://eprints.lse.ac.uk/id/eprint/55860

Actions (login required)

View Item View Item