International Advanced Researches and Engineering Journal,
Год журнала:
2025,
Номер
9(1), С. 1 - 11
Опубликована: Апрель 28, 2025
The
optimization
of
a
parabolic
trough
solar
power
plant
is
conducted
using
multi-objective
algorithm
in
this
study.
Initially,
the
design
plant,
planned
to
be
built
Afyonkarahisar
province,
developed.
Thermodynamic
and
thermo-economic
analyses
are
performed
based
on
design.
Key
variables
significantly
affecting
system's
outputs
identified
as
fluid
flow
rate
used
Organic
Rankine
Cycle
(ORC)
turbine
inlet
pressure.
A
parametric
study
carried
out
for
these
variables.
However,
optimizing
system
requires
more
than
just
parameters.
optimized
multi-objectively,
considering
all
relevant
graphical
applied
process.
For
base
case
values
30
kg/s
3500
kPa
pressure,
net
energy
production,
exergy
efficiency,
unit
cost
0.8443
MW,
2.32%,
0.2230
$/kWh,
respectively.
After
optimization,
best
results
achieved
at
42
pressure
4000
kPa.
case,
improve
1.228
3.37%,
0.1781
Energy & Environment,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 16, 2024
The
present
research
proposed
an
innovative
polygeneration
system
that
uses
solar,
geothermal,
and
natural
gas
energy
to
produce
power,
heat,
steam,
freshwater.
consists
of
a
proton
exchange
membrane
fuel
cell,
organic
Rankine
cycle,
multi-effect
thermal
desalination
system.
study
included
thermodynamic,
exergy,
exergoeconomic,
exergoenvironmental,
emergy-based
exergoenvironmental
factors
in
its
comprehensive
evaluation
the
Results
underscored
financial
aspect
cycle
cogeneration
system,
incurring
costs
0.4518
$/s
1.054
respectively,
while
also
highlighting
system's
capability
6
kg/s
environmental
impact
rates
were
quantified
for
at
0.1417
0.4814
pts/s
situating
within
ecological
context.
Further,
detailed
total
efficiency
net
power
output
ranging
between
32.45–33.51%
43.25–45.83%
efficiency,
56956–56322
kW
50174–51898
r
espectively,
showcasing
operational
capacity.
A
parametric
analysis
was
integral
study,
examining
key
parameters
on
functionality
thereby
providing
nuanced
understanding
performance
under
varying
scenarios.
