IET Generation Transmission & Distribution,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 30, 2024
Abstract
The
escalating
global
population
and
energy
demands
underscore
the
critical
role
of
renewable
sources,
particularly
solar
power,
in
mitigating
environmental
degradation
caused
by
traditional
fossil
fuels.
This
paper
emphasizes
advantages
energy,
especially
photovoltaic
(PV)
systems,
which
have
become
pivotal
hybrid
systems.
However,
accurate
modelling
identification
PV
cell
parameters
pose
challenges,
prompting
adoption
meta‐heuristic
optimization
algorithms.
work
explores
limitations
existing
algorithms
introduces
a
novel
approach,
bio‐dynamics
grasshopper
algorithm
(BDGOA).
BDGOA
addresses
deficiencies
both
exploration
exploitation
phases,
exhibiting
exceptional
convergence
speed
efficiency.
algorithm's
simplicity,
achieved
through
implementation
an
elimination
phase
controlled
search
space,
enhances
its
performance
without
intricate
calculations.
study
evaluates
applying
it
to
identify
unknown
five
modules.
effectiveness
is
demonstrated
extraction
for
RTC
France,
PWP201,
SM55,
KC200GT,
SW255
models,
validated
against
experimental
data
under
diverse
conditions.
concludes
with
insights
into
impact
radiation
temperature
on
module
parameters.
subsequent
sections
delve
intricacies
model,
articulate
formulation
proposed
algorithm,
present
simulations,
analyse
obtained
results.
emerges
as
promising
solution,
overcoming
contributing
significantly
advancement
efficient
parameter
identification,
thereby
propelling
progress
towards
sustainable
future.
Case Studies in Thermal Engineering,
Journal Year:
2024,
Volume and Issue:
60, P. 104647 - 104647
Published: June 4, 2024
A
novel
thermal
integration
approach
is
introduced
for
a
biomass-driven
gas
turbine
power
plant
that
generates
electricity,
coolant,
and
liquefied
hydrogen.
The
designed
scheme
encompassed
an
organic
flash
cycle,
bi-evaporator
ejector
refrigeration
unit,
high-temperature
water
electrolyzer
hydrogen
production,
multi-effect
desalination
cycle
supplying
electrolysis
process,
Claude
liquefaction.
system's
importance
comes
back
to
using
biomass
feedstock
as
the
input
fuel
utilizing
liquefaction
method.
In
addition
possibility
of
deploying
system
in
remote
areas,
it
provides
opportunity
storage
smaller
volume
more
accessible
transportation.
On
other
hand,
comparative
method
selecting
environmentally
friendly
fluid
heat
recovery
subsystem
another
crucial
aspect
present
study
from
environmental
aspect.
It
found
R161
appropriate
choice
among
seven
studied
working
fluids.
Subsequently,
comprehensive
evaluation
entire
thermodynamic
aspects
performed
intelligent
process.
By
considering
energy
exergy
efficiencies
along
with
CO2
emissions
objective
functions,
thorough
sensitivity
analysis
triple-objective
optimization
are
carried
out.
Hence,
artificial
neural
networks
objectives
developed
integrated
into
NSGA-II
Employing
LINMAP
decision-making,
values
attained,
exhibiting
39.6%
efficiency,
36.1%
631.7
kg/MWh
emissions.
Considering
optimum
solution,
proposed
capable
producing
cooling,
capacities
4526
kW,
1875
21.22
m3/day,
respectively.
Additionally,
scenario
yields
exergoenvironmental
index
0.579
exergetic
stability
0.61.
generation
rate
m3/day.
