(357b) An Investigation Into Periodic Operation of the Fischer-Tropsch Process | AIChE

(357b) An Investigation Into Periodic Operation of the Fischer-Tropsch Process

Authors 

Chakrabarti, D., University of Alberta
Han, F., University of Alberta
Kumar, S., University of Alberta
de Klerk, A., University of Alberta


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.

References

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).

See more of this Session: Modeling and Analysis of Chemical Reactors II

See more of this Group/Topical: Catalysis and Reaction Engineering Division