271911 An Investigation Into Periodic Operation of the Fischer-Tropsch Process

Tuesday, October 30, 2012: 3:35 PM
317 (Convention Center )
Debanjan Chakrabarti, Fei Han, Siddhartha Kumar, Arno de Klerk and Vinay Prasad, Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada

The Fischer-Tropsch (FT) process is a feed-to-liquids process which involves the conversion of syngas (CO+H2) to a hydrocarbon and oxygenate rich product with carbon numbers ranging from C1 to over C40. This product, known as syncrude, resembles conventional crude oil and can be refined to obtain petroleum products –gasoline, diesel, jet fuels and waxes. The syngas required for the process can be produced by reforming of natural gas, or gasification of coal, biomass or any carbonaceous waste. The gas loop thus consists of the feed, the syngas generation technology and the FT reactor (Figure 1)[1].

An industry operating this process would be interested in only a specific fraction of the wide product variety found in the syncrude. As such, it is of interest to optimize the process for the following metrics: (1) minimizing methane generation, (2) increasing distillate or naphtha cut selectivity in the syncrude, and (3) increasing conversion efficiency with respect to the feed. In order to do this, we investigate the strategy of periodic operation of the FT reactor. In addition, we explore optimization of the gas loop.

Periodic operations have been found in various studies to improve the selectivity of narrow product ranges in FT operation[2,3,4]. In this optimization strategy, we study the effect of periodic operations on the composition of the syncrude produced from the Fischer-Tropsch reactor. For this, we first perform a Computational Singular Perturbation study (CSP)[5] on a model of the Fischer-Tropsch Process. CSP is a numerical method which can be used to study the dynamic properties of a complex reaction system. It involves discretizing a kinetic model into various reaction modes, and grouping them into active and inactive modes, based on the timescales and amplitudes of each mode. The participation of each reaction and each species in each reaction mode can then be analyzed to infer which reactions and species contribute the most at a particular time instant. Based on this analysis, reduced kinetic models can be developed at each time instant. The CSP study is used in conjunction with experiment design to suggest the best frequency of periodic operation that would minimize methane generation and increase naphtha and distillate cut selectivity in the syncrude product; this can be achieved by focusing on chain-limiting reactions. Periodic operation using pulsing and sinusoidal variation of H2:CO ratios and reaction temperatures is investigated. Another concept we use for deciding on the optimal periodic operation strategy is employing analysis based on extents of reaction and incremental identification[6,7] for model reduction and experiment design.

For optimization of the gas loop, we model the different technologies (reactors) available in the gas loop and carry out studies to select optimized gas loops for the objectives mentioned above. The optimization is conducted at two levels, the selection of the appropriate combination of technologies for the units in the gas loop, and in the optimization of operating conditions for each reactor/process unit.


1.      A. de Klerk, Energy Environ. Sci., 4, 1177-1205 (2011).

2.      A.A. Adesina, R.R. Hudgins and P.L. Silveston, J. Chem. Tech. Biotechnol., 50, 535-547 (1991).

3.      M.J. van Vuuren and B.H. Davis, Fischer-Tropsch Synthesis: Catalysts and Catalysis, pp 201-215, B.H. Davis and M.L. Occelli (Eds), Elsevier (2007).

4.      A.A. Nikolopoulos, S.K. Gangwal and J.J. Spivey, Stud. Surf. Sci. Catal., 136, 351-356 (2001).

5.      S.H. Lam and D.A. Goussis, in Reduced Kinetic Mechanisms and Asymptotic Approximations for Methane-Air Flames, pp. 227-242, Springer Lecture Notes, M.O. Smooke (Ed.) (1991).

6.      M. Amrhein, N. Bhatt, B. Srinivasan and D. Bonvin, AIChE J., 56(11), 2873-2886 (2010).

7.      N. Bhatt, M. Amrhein and D. Bonvin, Ind. Eng. Chem. Res., 49(17), 7704-7717 (2010).

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