Results in Engineering,
Journal Year:
2024,
Volume and Issue:
22, P. 102067 - 102067
Published: March 31, 2024
In
this
research,
a
novel
initialization
strategy
for
conventional
MPPT
algorithms
is
proposed
to
define
the
best
position
tracking
process
start
over
P–V
curve.
Consequently,
global
maximum
power
point
(GMPP)
becomes
nearest
or
first
among
existing
multiple
MPPs
under
partial
shading
condition
(PSC).
addition,
step
size
of
applied
algorithm
minimized
based
on
its
proximity
actual
GMPP.
Therefore,
speed
improved,
and
loss
can
be
reduced
by
approach.
The
major
advantages
approach
are
eliminating
need
modify
original
algorithm,
hybridizing
with
other
algorithms,
employing
any
complex
procedures,
as
in
metaheuristic
optimization
algorithms.
Hence,
it
overcoming
main
drawbacks
MPPT.
work,
simplest
technique,
which
perturbation
observation
(P&O)
show
enhancement
performance
without
introduce
processes.
MATLAB/Simulink
simulation
model
hardware
implementation
digital
signal
processing
(DSP)
controller
TMS320F28335
two
distinct
methodologies
used
validate
outperformance
when
applying
technique
PSC
various
weather
fluctuations.
outcomes
that
was
successful
extracting
peak
while
also
improving
time
response,
accuracy,
generating
oscillations.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: April 8, 2024
Abstract
This
paper
proposes
an
innovative
approach
to
improve
the
performance
of
grid-connected
photovoltaic
(PV)
systems
operating
in
environments
with
variable
atmospheric
conditions.
The
dynamic
nature
parameters
poses
challenges
for
traditional
control
methods,
leading
reduced
PV
system
efficiency
and
reliability.
To
address
this
issue,
we
introduce
a
novel
integration
fuzzy
logic
sliding
mode
methodologies.
Fuzzy
enables
effectively
handle
imprecise
uncertain
data,
allowing
decision-making
based
on
qualitative
inputs
expert
knowledge.
Sliding
control,
known
its
robustness
against
disturbances
uncertainties,
ensures
stability
responsiveness
under
varying
Through
these
methodologies,
our
proposed
offers
comprehensive
solution
complexities
posed
by
real-world
dynamics.
We
anticipate
applications
across
various
geographical
locations
climates.
By
harnessing
synergistic
benefits
promises
significantly
enhance
reliability
presence
On
grid
side,
both
PSO
(Particle
Swarm
Optimization)
GA
(Genetic
Algorithm)
algorithms
were
employed
tune
current
controller
PI
(Proportional-Integral)
(inverter
control).
Simulation
results,
conducted
using
MATLAB
Simulink,
demonstrate
effectiveness
hybrid
MPPT
technique
optimizing
system.
exhibits
superior
tracking
efficiency,
achieving
convergence
time
0.06
s
99.86%,
less
oscillation
than
classical
methods.
comparison
other
techniques
highlights
advantages
approach,
including
higher
faster
response
times.
simulation
outcomes
are
analyzed
strategies
sides
(the
array
side).
Both
offer
effective
methods
tuning
controller.
According
considered
IEEE
standards
low-voltage
networks,
total
harmonic
distortion
values
(THD)
obtained
considerably
high
(8.33%
10.63%,
algorithms,
respectively).
Comparative
analyses
terms
stability,
rapid
changes.
IEEE Access,
Journal Year:
2024,
Volume and Issue:
12, P. 6148 - 6159
Published: Jan. 1, 2024
Considering
photovoltaic
systems'
sustainability
and
environmental
friendliness,
they
have
been
widely
used
due
to
ease
of
installation
as
their
cost
reduces
efficiency
is
improved.
Analytical
maximum
power
point
tracking
methods
for
system
work
effectively
under
uniform
weather
conditions.
However,
may
fall
into
local
points
partial
shading
Although
numerous
meta-heuristic
can
overcome
these
challenges,
still
be
improved
regarding
the
convergence
time
global
point.
This
paper
suggests
an
grey
wolf
optimization
method
track
points,
enhancing
process
various
The
proposed
has
verified
experimentally
dynamic
real
conditions,
consisting
non-uniform
provides
better
speed
up
82%
1.4%
compared
basic
optimization.
According
daily
performance
evaluation,
IGWO
runtime
by
76%
improves
energy
harvesting
2.3%
obtained
results
validate
superiority
conditions
in
terms
accuracy.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Jan. 25, 2025
This
study
first
proposes
an
innovative
method
for
optimizing
the
maximum
power
extraction
from
photovoltaic
(PV)
systems
during
dynamic
and
static
environmental
conditions
(DSEC)
by
applying
horse
herd
optimization
algorithm
(HHOA).
The
HHOA
is
a
bio-inspired
technique
that
mimics
motion
cycles
of
entire
horses.
Next,
linear
active
disturbance
rejection
control
(LADRC)
was
applied
to
monitor
HHOA's
reference
voltage
output.
LADRC,
known
managing
uncertainties
disturbances,
improves
anti-interference
capacity
point
tracking
(MPPT)
speeds
up
system's
response
rate.
Then,
in
comparison
traditional
(perturb
&
observe;
P&O)
metaheuristic
algorithms
(conventional
particle
swarm
optimization;
CPSO,
grasshopper
GHO,
deterministic
PSO;
DPSO)
through
DSEC,
simulations
results
demonstrate
combination
HHOA-LADRC
can
successfully
track
global
peak
(GMP)
with
less
fluctuations
quicker
convergence
time.
Finally,
experimental
investigation
proposed
accomplished
NI
PXIE-1071
Hardware-In-Loop
(HIL)
prototype.
output
findings
show
effectiveness
provided
may
approach
value
higher
than
99%,
showed
rate
converging
oscillations
detection
mechanism.
