Research Square (Research Square),
Год журнала:
2023,
Номер
unknown
Опубликована: Апрель 25, 2023
Abstract
Solar
energy
offers
several
environmental,
economic,
and
security
advantages.
Parasitic
parameters
shading
on
solar
panels
can
reduce
efficiency.
This
paper
presents
a
bio-inspired
Enhanced
Slime
Mold
(ESM)
algorithm
search
strategy
to
find
the
optimal
power
point
by
simulating
behaviour
of
slime
molds
in
virtual
environment.
In
panel,
proposed
ESM
provides
not
only
for
parameter
extraction
but
also
serves
as
Maximum
Power
Point
Tracking
(MPPT)
during
Partial
Shading
Conditions
(PSC).
Proposed
dynamic
is
examined
under
irradiation
various
temperature
conditions.
The
effectiveness
technique
has
been
validated
extracting
from
conventional
polycrystalline
monocrystalline
modules
form
5S-5P
arrangement.
instance
MPPT
operation,
compared
with
Ant
Bee
Colony
Perturb&
Observe
(ABC-PO)
determine
its
efficacy.
Moreover,
unknown
cell
existing
optimization
algorithms
such
Artificial
Swarm
Optimization
(ABC
SO),
Genetic
Algorithm
(GA),
Covariant
Matrix
(CM),
(ABC),
Advanced
Particle
(APSO).
this
connection,
superior
above-mentioned
due
high
accuracy,
smaller
number
computations,
minimum
computational
time.
IET Renewable Power Generation,
Год журнала:
2024,
Номер
18(15), С. 3329 - 3354
Опубликована: Окт. 19, 2024
Abstract
This
study
presents
a
new
Maximum
Power
Point
Tracking
(MPPT)
approach
for
solar
photovoltaic
(PV)
systems,
combining
the
Super‐Twisting
Algorithm
(STA)
and
Grey
Wolf
Optimizer
(GWO).
The
STA‐GWO‐MPPT
method
improves
efficiency
in
dynamic
conditions
by
using
STA
control
GWO
parameter
optimization,
enhancing
stability
robustness.
Performance
evaluation
is
conducted
through
MATLAB/Simulink
simulations
experimental
validation
on
small‐scale
test
bench.
Various
quantitative
metrics,
including
rise
time,
settling
power
production,
efficiency,
root
mean
square
error
(RMSE),
standard
deviation
(STD),
are
employed
assessment.
Results
indicate
significantly
faster
convergence
speeds
proposed
compared
to
conventional
MPPT
techniques.
Specifically,
time
0.0129
seconds,
outperforming
Fuzzy
Logic
Control
(FLC)
(0.2638
seconds)
with
Sliding
Mode
(GWO‐SMC)
(0.0181
seconds).
Additionally,
exhibits
superior
tracking
an
average
of
99.33%,
surpassing
FLC
(96.93%)
GWO‐SMC
(99.19%).
Moreover,
it
reduces
fluctuations,
RMSE
7.819%
STD
6.547%,
(RMSE:
13.471%,
STD:
4.519%)
8.507%,
6.108%).
Overall,
this
contributes
valuable
insights
into
PV
implications
both
research
practical
applications.
International Journal of Computer Applications,
Год журнала:
2023,
Номер
184(42), С. 39 - 48
Опубликована: Янв. 25, 2023
Maximum
Power
Point
Tracking
(MPPT)
algorithms
are
utilized
in
solar
photovoltaic
systems
to
enhance
the
overall
performance.Various
conventional
MPPT
employed
systems.Nevertheless,
those
futile
Partial
Shaded
condition
(PSC)
and
impotent
identifying
maximum
power
point.Also,
failed
bi-furcate
local
global
maxima
during
partial
shaded
condition.The
impact
of
shading
results
false
selection
extreme
points
sources,
total
efficiency
PV
system
comes
down.The
researchers'
advanced
algorithm
overcomes
algorithm.This
research
deals
with
comparative
analysis
Artificial
Intelligence
based
(AI
MPPT)
by
considering
parameters
such
as
speed
convergence,
tracking
accuracy,
cost
implementation,
efficiency.Moreover,
issues
challenges
selecting
an
optimized
discussed
this
work.The
performance
evaluated
individually.The
fuzzy
logic-based
performs
better
than
other
algorithms.
Energy Sources Part A Recovery Utilization and Environmental Effects,
Год журнала:
2023,
Номер
45(4), С. 10217 - 10241
Опубликована: Авг. 7, 2023
ABSTRACTPartial
shading
condition
(PSC)
leads
to
mismatch
losses
and
multiple
peaks
on
the
output
curves.
Several
static-based
reconfigurations
like
total
cross-tied
(TCT),
skyscraper
reconfiguration
(SSR),
odd-even
(OER)
were
reported
address
these
issues.
But,
less
shade
dispersion
more
wiring
occur
in
arrays.
This
work
focuses
both
power
improvement
wire
length
reduction
of
solar
arrays
under
PSC.
Based
reduced
than
50%
for
SSR
over
OER,
a
novel
enhanced
(ESR)
is
proposed
this
work.
ESR
cheaper
by
169.13
INR
1699.07
as
compared
OER
respectively.
Further,
performance
obtaining
several
parameters
fill
factor
(FF),
efficiency
(Ƞ),
global
(GP),
execution
ratio
(ER),
current
loss
(IL),
(ML)
with
existing
OER.
It
observed
that
Ƞ
improved
4%
13.05%
GP
maximized
3.74W
4.48W
novel-proposed
which
experimentally
verified
regional
corner
shadings
Overall,
confirms
its
supremacy
other
considered
models
study.KEYWORDS:
Cost
analysisefficiencypartial
conditionssolar
arraywiring
Disclosure
statementNo
potential
conflict
interest
was
author(s).Additional
informationNotes
contributorsVijay
Laxmi
MishraVijay
Mishra
received
M.
Tech
degree
Power
System
from
Shri
Ramswaroop
Memorial
University,
Lucknow,
Uttar
Pradesh,
India
2016.
She
currently
pursuing
Ph.D.
Electrical
Engineering
Kamla
Nehru
Institute
Technology,
Sultanpur,
Homi
Bhabha
Research
cum
Teaching
Fellowship
scheme.
Her
research
interests
include
electric
systems,
photovoltaic
load
forecasting.Yogesh
K.
ChauhanYogesh
Chauhan
Tech.
Electronics
Drives
IITD,
New
Delhi,
Induction
Generator
Thapar
Patiala,
India,
1998
2010,
Currently
he
working
Professor
Head
Department
EED
at
KNIT,
Sultanpur.
He
having
20
years
teaching/research
experience.
His
electronics
converters
drives,
induction
generators,
renewable
energy-based
electrical
generation.K.S.
VermaK.
S.
Verma
Systems
KNIT
Ph.
D
FACTS
devices
Indian
Roorkee,
2003
Presently
department
Director
Sultanpur
India.
flexible
AC
transmission
planning,
operation
distributed
generation,
modeling
&
simulation
systems.
2022 7th International Conference on Power and Renewable Energy (ICPRE),
Год журнала:
2023,
Номер
unknown
Опубликована: Сен. 22, 2023
Aiming
at
the
problems
of
traditional
maximum
power
point
tracking
(MPPT)
algorithm
for
photovoltaic
systems,
such
as
poor
accuracy,
long
convergence
time,
large
steady-state
oscillation,
and
difficulty
converging
to
global
point.
This
paper
presents
a
reinforcement
learning
(RL)
method
based
on
deep
Q
network
(DQN)
improve
optimize
MPPT
algorithm.
In
this
method,
problem
systems
is
transformed
into
Markov
decision
process
(MDP),
circuit
composed
cell
DC-DC
boost
converter
set
training
environment.
The
DQN
with
continuous
state
discrete
action
space
selected
train
Through
modeling
simulation
in
MATLAB/Simulink,
feasibility
effectiveness
are
proved
under
different
solar
irradiance
variation
levels.
Compared
perturbation
observation
(P&O)
incremental
conductance
(INC),
accuracy
significantly
improved.
particle
swarm
optimization
(PSO)
grey
wolf
(GWO),
it
verified
that
proposed
can
converge
(GMPP)
faster
has
better
performance
non-uniform
irradiance.
Research Square (Research Square),
Год журнала:
2023,
Номер
unknown
Опубликована: Апрель 25, 2023
Abstract
Solar
energy
offers
several
environmental,
economic,
and
security
advantages.
Parasitic
parameters
shading
on
solar
panels
can
reduce
efficiency.
This
paper
presents
a
bio-inspired
Enhanced
Slime
Mold
(ESM)
algorithm
search
strategy
to
find
the
optimal
power
point
by
simulating
behaviour
of
slime
molds
in
virtual
environment.
In
panel,
proposed
ESM
provides
not
only
for
parameter
extraction
but
also
serves
as
Maximum
Power
Point
Tracking
(MPPT)
during
Partial
Shading
Conditions
(PSC).
Proposed
dynamic
is
examined
under
irradiation
various
temperature
conditions.
The
effectiveness
technique
has
been
validated
extracting
from
conventional
polycrystalline
monocrystalline
modules
form
5S-5P
arrangement.
instance
MPPT
operation,
compared
with
Ant
Bee
Colony
Perturb&
Observe
(ABC-PO)
determine
its
efficacy.
Moreover,
unknown
cell
existing
optimization
algorithms
such
Artificial
Swarm
Optimization
(ABC
SO),
Genetic
Algorithm
(GA),
Covariant
Matrix
(CM),
(ABC),
Advanced
Particle
(APSO).
this
connection,
superior
above-mentioned
due
high
accuracy,
smaller
number
computations,
minimum
computational
time.
