The
assessment
of
photovoltaic
devices,
which
convert
light
energy
into
electricity,
becomes
significantly
relevant
due
to
the
aspiration
reduce
pollution
on
a
global
scale.
In
this
context,
pursuit
optimizing
efficiency
in
converting
electrical
involves
exhaustive
studies
and
structural
analyses
solar
cells,
all
directed
toward
achieving
goal.
This
study
introduces
research
proposal
aimed
at
analyzing
losses
associated
with
series
resistance
(Rs).
analysis
takes
account
each
component
comprising
resistance,
pro-posing
network
resistances
that
precisely
models
these
elements.
aforementioned
focused
simple-structured
crystalline
silicon
cells.
During
investigation,
junction
depth
(xj)
n-p
materials
was
varied
aim
efficiencies
range
12%.
However,
desired
efficiency,
significant
impact
observed
when
I-V
curves
cells
obtained
manufacturing
process.
Engineering Research Express,
Journal Year:
2024,
Volume and Issue:
6(2), P. 025316 - 025316
Published: April 16, 2024
Abstract
This
work
proposes
an
application
of
Fractional
Order
Particle
Swarm
Optimization
(FO-PSO),
a
meta-heuristic
method
for
parameters
estimation
photo-voltaic
(PV)
module
as
non-linear,
transcendental,
multi-modal
and
implicit
optimization
problem.
The
uses
single
diode
model
(SDM),
double
(DDM)
three-diode
(TDM)
PV
modules
with
the
constraint
that
only
data-sheet
information
may
be
utilized.
A
fitness
function
based
on
error
amongst
computed
values
current
voltage
ones
given
in
characteristic
I-V
curves
data-sheet,
is
minimized
using
FO-PSO
to
get
required
parameters.
comparative
study
between
estimated
provided
by
manufacturers
will
determine
effectiveness
this
research.
demonstrated
comparing
other
techniques.
technique
makes
novel
contribution
power
systems
industry
making
it
possible
obtain
nearly
realistic
any
commercial
module.
determined
results
all
three
models
state
art
Root
Mean
Square
calculated
TDM
less
than
10e–16,
producing
very
consistent
results.
Therefore,
anticipated
competitive
obtaining
specifications.
Sensors,
Journal Year:
2023,
Volume and Issue:
23(7), P. 3657 - 3657
Published: March 31, 2023
Photovoltaic
(PV)
panels
have
been
widely
used
as
one
of
the
solutions
for
green
energy
sources.
Performance
monitoring,
fault
diagnosis,
and
Control
Operation
at
Maximum
Power
Point
(MPP)
PV
became
popular
research
topics
in
past.
Model
parameters
could
reflect
health
conditions
a
panel,
model
parameter
estimation
can
be
applied
to
panel
diagnosis.
In
this
paper,
we
will
propose
new
algorithm
by
using
Neural
Network
(ANN)
with
Numerical
Current
Prediction
(NCP)
layer.
Output
voltage
current
signals
(VI)
after
load
perturbation
are
observed.
An
ANN
is
trained
estimate
parameters,
which
then
fined
tuned
NCP
improve
accuracy
about
6%.
During
testing
stage,
VI
input
into
proposed
ANN-NCP
system.
estimated
algorithms,
detection,
tracking
operating
points
MPP
conditions.
The
assessment
of
photovoltaic
devices,
which
convert
light
energy
into
electricity,
becomes
significantly
relevant
due
to
the
aspiration
reduce
pollution
on
a
global
scale.
In
this
context,
pursuit
optimizing
efficiency
in
converting
electrical
involves
exhaustive
studies
and
structural
analyses
solar
cells,
all
directed
toward
achieving
goal.
This
study
introduces
research
proposal
aimed
at
analyzing
losses
associated
with
series
resistance
(Rs).
analysis
takes
account
each
component
comprising
resistance,
pro-posing
network
resistances
that
precisely
models
these
elements.
aforementioned
focused
simple-structured
crystalline
silicon
cells.
During
investigation,
junction
depth
(xj)
n-p
materials
was
varied
aim
efficiencies
range
12%.
However,
desired
efficiency,
significant
impact
observed
when
I-V
curves
cells
obtained
manufacturing
process.
