CO2
emissions
are
regarded
as
one
of
the
key
factors
that
affect
global
warming.
Significant
efforts
have
been
made
to
develop
efficient
and
economically
attractive
technologies
to
reduce
to
CO2
emissions.
Post-combustion
MEA-based
CO2
capture
is
regarded
as
a
realistic
and
viable
technology
that
can
be
implemented
to
capture
CO2
from
existing
coal-fired
power
plants.
My
research
is
focused
on
the
development
of
dynamic
flexibility
studies
for
post-combustion
MEA-based
CO2
capture
plants.
The
flexibility
analyses
considered
in
my
research
have
made
use
of
Model
Predictive
Controllers
(MPC),
which
is
at
the
state-of-the-art
in
process
control.
Although
MPC
has
been
widely
applied
to
processes
from
different
sectors,
its
implementation
in
CO2
capture
plants
is
relatively
new;
hence
the
motivation
to
demonstrate
its
applicability
and
significant
benefits
for
this
type
of
processes.
In
addition,
I
also
pursue
in
my
research
the
development
of
simultaneous
scheduling
and
control
frameworks
for
the
design
of
optimal
operating
and
control
policies
for
post-combustion
CO2
capture
plants.
As
shown
in
the
figure
below,
our
current
scheduling
and
control
framework
have
shown
to
improve
the
dynamic
performance
of
a
CO2
plant
when
compared
to
that
obtained
from
a
traditional
sequential
scheduling
and
control
approach.
Thesis: Modelling,
Scheduling
and
Control
of
Pilot-Scale
and
Commercial-Scale
MEA-based
CO2
Capture
Plants
