(24d) Analysis of a Simulated Moving Bed Configuration for Chemical-Looping Combustion | AIChE

(24d) Analysis of a Simulated Moving Bed Configuration for Chemical-Looping Combustion

Authors 

Palmer, C. - Presenter, University of Connecticut
Han, L. - Presenter, University of Connecticut
Bollas, G. M. - Presenter, University of Connecticut

The
impact of greenhouse gas emissions from power generation plants motivates the
need for energy production technologies with carbon capture and sequestration. Chemical-looping
combustion (CLC) is an emerging method for energy production using fossil fuels
with inherent separation of CO2. CLC utilizes an intermediate metal oxide
oxygen carrier and a reduction-oxidation cycle to prevent direct contact of air
and fuel during the combustion process. In the reduction step, a hydrocarbon
fuel (i.e., CH4) is oxidized by the oxygen carrier (i.e., NiO),
yielding CO2 and H2O. In the subsequent oxidation step, the
reduced oxygen carrier (i.e., Ni) is regenerated in air, emitting N2
and unreacted O2. A pure stream of CO2 can be obtained
after the reduction step after condensation of H2O without a large
energy penalty or additional separation steps.

Multiple
reactor designs have been proposed for CLC, including interconnected
fluidized bed processes [1], alternating
flow fixed-bed processes [2], and moving bed
processes [3]. The
constraints and implications relating to oxygen carrier particle size, reactor
size, and operating conditions vary among these implementations, resulting in different
fuel conversions, CO2 capture efficiencies and additional separation
steps required for CO2 capture. For example, the moving bed reactor
utilizes countercurrent flows of fuel and solids to maximize the thermodynamic
driving force of the reactions in the CLC reducer, achieving higher
efficiencies than fluidized beds. CO2 selectivity is greatly
increased because the hydrocarbon fuel is always introduced to fresh oxygen
carrier. However, circulation of solids within a reactor often leads to operational
challenges, such as product stream contamination, gas leakage, and high
particle abrasion. The simulated moving bed reactor, shown in Figure 1a,
is an adaption of the moving bed reactor with stationary solid particles in a
fixed-bed configuration. This process consists of switching the inlet and
outlet ports simultaneously along the axial dimension of a standard fixed-bed (Figure
1b
) to simulate the countercurrent movement of gas and solids. Simulated
moving bed reactors have been proven to increase efficiencies and overcome
equilibrium restrictions for reactions in absorption, adsorption and extraction
processes, such as reactive chromatography [4].

Figure 1: Reactor designs for CLC: (a) simulated
moving bed and (b) fixed-bed

In
this work, the simulated moving bed design concept is explored as a reactor
option for gaseous CLC. A single fixed-bed configuration (Figure 1b) is
used as a benchmark for comparison of reactor performance. A simulated
moving bed reactor is modeled using multiple fixed-bed reactors in the
configuration shown in Figure 1a. A one-dimensional, homogeneous fixed-bed
reactor model with axial dispersion, energy balance and momentum balance is
used in concert with CLC reduction and oxidation kinetics of NiO with CH4 and
air derived previously, using literature and in-house fixed-bed reactor data [5?7]. The
configuration of the baseline fixed bed reactor is representative of existing reactors
reported in the literature. The performance of the simulated moving bed reactor
is then compared to its fixed bed counterpart in terms of CH4
conversion, CO2 capture efficiency, oxygen carrier conversion and
selectivity to solid carbon. The reactor temperature profiles are also explored
to identify advantages in the proposed setup in terms of heat utilization
within and between the reactors.

Figure 2: Fuel conversion (A), CO2 gas
selectivity (B) and solid carbon selectivity (C) vs.

bed NiO conversion for fixed-bed
and simulated moving bed (SMB) processes at 900°C

Application
of the simulated moving bed technology yields numerous benefits over its fixed-bed
counterpart with a negligible sacrifice to fuel conversion, as shown in Figure
2a
. First, the SMB achieves higher CO2 selectivity at
high NiO conversions (Figure 2b). As the inlet and outlet ports are
switched along the length of the reactor, the inlet feed is constantly
introduced to fresh oxygen carrier, which promotes the conversion to CO2
and suppresses the catalytic reactions that yield partial oxidation products. As
a result, the second benefit is the reduction in carbon deposition during the
reduction cycle. A comparison to the fixed-bed performance is shown in Figure
2c
. By recycling the combustion products (i.e., CO2 and H2O)
throughout the NiO-depleted regions of the reactor, any solid carbon formed
previously is gasified. Another advantage of the simulated moving bed process is
the mitigation of cold spots inside the reactor, as shown in Figure 3. The
reduction reactions with NiO are generally endothermic, so a cold zone is
exhibited when fuel is in contact with NiO. However, in the SMB concept, the
reaction zone covers a larger area so the extent of the temperature change is
reduced and circulation of hot gases within the converted zones further warms
up the bed (Figure 3).

Figure 3: Transient
temperature distributions for one CLC reduction step at 900°C

with fixed-bed
(left) and simulated moving bed (SMB) (right) processes

 

In
summary, the simulated moved bed reactor design is shown to be promising for
CLC applications and future work is aimed at implementation for multiple CLC
reduction-oxidation cycles and optimization studies of the novel design. In
this presentation, a proof of concept analysis will be illustrated with case
studies comparing the operation of a fixed-bed process with that of a simulated
moving bed, where total reactor size, oxygen carrier loading, methane capacity,
temperature and pressure are kept the same.

 

 

 

 

Acknowledgements:
This
material is based upon work supported by the National Science Foundation under
Grant No. 1054718 and the UConn Prototype Fund.

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