Sustainability,
Journal Year:
2023,
Volume and Issue:
15(7), P. 5732 - 5732
Published: March 24, 2023
For
many
electrical
systems,
such
as
renewable
energy
sources,
their
internal
parameters
are
exposed
to
degradation
due
the
operating
conditions.
Since
model’s
accuracy
is
required
for
establishing
proper
control
and
management
plans,
identifying
a
critical
prominent
task.
Various
techniques
have
been
developed
identify
these
parameters.
However,
metaheuristic
algorithms
received
much
attention
use
in
tackling
wide
range
of
optimization
issues
relating
parameter
extraction.
This
work
provides
an
exhaustive
literature
review
on
solving
extraction
utilizing
recently
algorithms.
paper
includes
newly
published
articles
each
studied
context
its
discussion.
It
aims
approve
applicability
make
understanding
deployment
easier.
there
not
any
exact
that
can
offer
satisfactory
performance
all
issues,
especially
problems
large
search
space
dimensions.
As
result,
capable
searching
very
spaces
possible
solutions
thoroughly
investigated
review.
Furthermore,
depending
behavior,
divided
into
four
types.
These
types
details
included
this
paper.
Then,
basics
identification
process
presented
discussed.
Fuel
cells,
electrochemical
batteries,
photovoltaic
panel
analyzed.
Heliyon,
Journal Year:
2024,
Volume and Issue:
10(3), P. e25407 - e25407
Published: Feb. 1, 2024
Integration
of
photovoltaic
(PV)
systems,
desalination
technologies,
and
Artificial
Intelligence
(AI)
combined
with
Machine
Learning
(ML)
has
introduced
a
new
era
remarkable
research
innovation.
This
review
article
thoroughly
examines
the
recent
advancements
in
field,
focusing
on
interplay
between
PV
systems
water
within
framework
AI
ML
applications,
along
it
analyses
current
to
identify
significant
patterns,
obstacles,
prospects
this
interdisciplinary
field.
Furthermore,
incorporation
methods
improving
performance
systems.
includes
raising
their
efficiency,
implementing
predictive
maintenance
strategies,
enabling
real-time
monitoring.
It
also
explores
transformative
influence
intelligent
algorithms
techniques,
specifically
addressing
concerns
pertaining
energy
usage,
scalability,
environmental
sustainability.
provides
thorough
analysis
literature,
identifying
areas
where
is
lacking
suggesting
potential
future
avenues
for
investigation.
These
have
resulted
increased
decreased
expenses,
improved
sustainability
system.
By
utilizing
artificial
intelligence
freshwater
productivity
can
increase
by
10
%
efficiency.
offers
informative
perspectives
researchers,
engineers,
policymakers
involved
renewable
technology.
sheds
light
latest
desalination,
which
are
facilitated
ML.
The
aims
guide
towards
more
sustainable
technologically
advanced
future.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Feb. 11, 2024
Abstract
The
parameter
identification
problem
of
photovoltaic
(PV)
models
is
classified
as
a
complex
nonlinear
optimization
that
cannot
be
accurately
solved
by
traditional
techniques.
Therefore,
metaheuristic
algorithms
have
been
recently
used
to
solve
this
due
their
potential
approximate
the
optimal
solution
for
several
complicated
problems.
Despite
that,
existing
still
suffer
from
sluggish
convergence
rates
and
stagnation
in
local
optima
when
applied
tackle
problem.
study
presents
new
estimation
technique,
namely
HKOA,
based
on
integrating
published
Kepler
algorithm
(KOA)
with
ranking-based
update
exploitation
improvement
mechanisms
estimate
unknown
parameters
third-,
single-,
double-diode
models.
former
mechanism
aims
at
promoting
KOA’s
exploration
operator
diminish
getting
stuck
optima,
while
latter
strengthen
its
faster
converge
solution.
Both
KOA
HKOA
are
validated
using
RTC
France
solar
cell
five
PV
modules,
including
Photowatt-PWP201,
Ultra
85-P,
STP6-120/36,
STM6-40/36,
show
efficiency
stability.
In
addition,
they
extensively
compared
techniques
effectiveness.
According
experimental
findings,
strong
alternative
method
estimating
because
it
can
yield
substantially
different
superior
findings
Energies,
Journal Year:
2022,
Volume and Issue:
15(23), P. 8941 - 8941
Published: Nov. 25, 2022
Currently,
solar
energy
is
one
of
the
leading
renewable
sources
that
help
support
transition
into
decarbonized
systems
for
a
safer
future.
This
work
provides
comprehensive
review
mathematical
modeling
used
to
simulate
performance
photovoltaic
(PV)
modules.
The
meteorological
parameters
influence
PV
modules
are
also
presented.
Various
deterministic
and
probabilistic
methodologies
have
been
investigated.
Moreover,
metaheuristic
methods
in
parameter
extraction
diode
models
equivalent
circuits
addressed
this
article
encourage
adoption
algorithms
can
predict
with
highest
precision
possible.
With
significant
increase
computational
power
workstations
personal
computers,
soft
computing
expected
attract
more
attention
dominate
other
algorithms.
different
error
expressions
formulating
objective
functions
employed
extracting
comprehensively
expressed.
Finally,
aims
develop
layout
previous,
current,
possible
future
areas
module
modeling.
