Accurate parameters extraction of photovoltaic models using Lambert W-function collaborated with AI-based Puma optimization method
Results in Engineering,
Год журнала:
2025,
Номер
unknown, С. 104268 - 104268
Опубликована: Фев. 1, 2025
Язык: Английский
Enhanced Single-Diode Model for Improved Accuracy in Photovoltaic Cell Characterization
e-Prime - Advances in Electrical Engineering Electronics and Energy,
Год журнала:
2025,
Номер
unknown, С. 100935 - 100935
Опубликована: Фев. 1, 2025
Язык: Английский
Improved Tasmanian devil optimization method for accurate parameter extraction of photovoltaic models in various temperature and irradiation conditions
International Journal of Modelling and Simulation,
Год журнала:
2025,
Номер
unknown, С. 1 - 28
Опубликована: Фев. 26, 2025
High-performance
solar
photovoltaic
models
rely
on
a
precise
understanding
of
(PV)
cell
parameters.
This
necessity
arises
from
the
importance
comprehending
and
optimizing
performance
systems
to
ensure
reliable
efficient
energy
production.
Nonetheless,
due
intrinsic
nonlinear
nature
systems,
employing
algorithm
is
essential
for
accurate
modeling.
In
this
article,
an
enhanced
inspired
by
behavior
Tasmanian
Devil,
named
Improved
Devil
Optimization
(ITDO),
proposed
enhance
original
TDO.
Our
includes
improvements
exploitation
phase,
increasing
frequency
prey
detection
attacks
in
target
zone.
The
method
retains
steps,
with
exploration
stage
unchanged.
However,
second
step
has
been
adaptation
mechanism,
final
improved
efficiently
select
global
optimum.
These
modifications
do
not
impact
method's
complexity.
To
assess
ITDO's
effectiveness,
experiments
were
conducted
using
single,
double,
PV
module
models.
Thorough
comparison
seven
other
algorithms
revealed
superior
solution
accuracy.
Additionally,
statistical
analyses
Wilcoxon
rank-sum
Friedman
tests
confirmed
superiority
as
most
robust
parameter
estimation
systems.
Язык: Английский
Electrical characterization of photovoltaic generators using the improved dwarf mongoose optimization algorithm: A novel approach to parameter extraction across diverse PV models
International Journal of Hydrogen Energy,
Год журнала:
2025,
Номер
112, С. 354 - 368
Опубликована: Март 1, 2025
Язык: Английский
Optimizing parameter extraction in proton exchange membrane fuel cell models via differential evolution with dynamic crossover strategy
Energy,
Год журнала:
2025,
Номер
unknown, С. 135397 - 135397
Опубликована: Март 1, 2025
Язык: Английский
An Analytical-Iterative Method for Accurate Parameter Estimation of the Single-Diode Model in Photovoltaic Modules: Application to Monocrystalline and Polycrystalline Modules under Various Environmental Conditions
Green Energy and Intelligent Transportation,
Год журнала:
2025,
Номер
unknown, С. 100285 - 100285
Опубликована: Март 1, 2025
Язык: Английский
Boosting Walrus Optimizer Algorithm based on ranking-based update mechanism for parameters identification of photovoltaic cell models
Electrical Engineering,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 9, 2024
Язык: Английский
Parameter Extraction of Photovoltaic Cell and Module with Four Diode Model Using Flood Algorithm
Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 5, 2024
Photovoltaic
(PV)
cells
exhibit
a
nonlinear
characteristic.
Before
modeling
these
cells,
obtaining
accurate
parameters
is
essential.
During
the
phase,
using
crucial
for
accurately
characterizing
and
reflecting
behavior
of
PV
structures.
Therefore,
this
article
focuses
on
parameter
extraction.
A
cell
module
were
selected
modeled
four-diode
model
(FDM).
This
problem,
consisting
eleven
unknown
related
to
FDM,
was
solved
with
flood
algorithm
(FLA).
To
compare
algorithm’s
performance
same
polar
lights
optimizer
(PLO),
moss
growth
optimization
(MGO),
walrus
(WO),
educational
competition
(ECO)
also
employed.
These
five
metaheuristic
algorithms
used
first
time
in
study,
both
solving
extraction
problem
FDM.
The
objective
function
aimed
at
smallest
root
mean
square
error
(RMSE)
evaluated
compared
through
assessment
metrics,
computational
accuracy,
time,
statistical
methods.
minimum
RMSE
obtained
FLA,
calculated
as
9.8251385E-04
FDM-C
1.6884311E-03
FDM-M.
statistically
demonstrate
reinforce
FLA’s
success
over
other
algorithms,
Friedman
test
Wilcoxon
signed-rank
utilized.
According
tests,
FLA
produced
significantly
better
results
than
outperformed
them
pairwise
comparisons.
In
conclusion,
has
proven
be
successful
promising
extraction,
its
validated.
Язык: Английский